Except where noted, all photographs courtesy of Donald O. Rosenberry, 

U.S. Geological Survey.

Cover artwork by John M. Evans, U.S. Geological Survey, retired.
Field Techniques for Estimating Water 

Fluxes Between Surface Water and 

Ground Water

Edited by Donald O. Rosenberry and James W. LaBaugh

Techniques and Methods 4–D2

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2008

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Suggested citation:

Rosenberry, D.O., and LaBaugh, J.W., 2008, Field techniques for estimating water fluxes between surface water 

and ground water: U.S. Geological Survey Techniques and Methods 4–D2, 128 p.

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iii

Contents

1. Introduction and Characteristics of Flow.................................................................................1

 By James W. LaBaugh and Donald O. Rosenberry

2. Use of Monitoring Wells, Portable Piezometers, and Seepage Meters 

to Quantify Flow Between Surface Water and Ground Water............................................39

 By Donald O. Rosenberry, James W. LaBaugh, and Randall J. Hunt

3. Hydrogeologic Characterization and Methods Used in the Investigation 

of Karst Hydrology...............................................................................................................71

 By Charles J. Taylor and Earl A. Greene

4. Analysis of Temperature Gradients to Determine Stream Exchanges 

with Ground Water...................................................................................................................115

 By James Constantz, Richard Niswonger, and Amy E. Stewart
iv

Conversion Factors, Definitions, and Abbreviations

Inch/Pound to SI

Multiply By To obtain

Length

kilometer (km) 0.6214 mile (mi)

meter (m) 3.281 foot (ft)

centimeter (cm) 0.3937 inch (in)

millimeter (mm) 0.03937 inch (in)

Area

square kilometer (km2

) 0.3861 square mile (mi2)

square meter (m2

) 10.76 square foot (ft2)

square centimeter (cm2

) 0.1550 square inch (in2)

square centimeter (cm2

) 0.001076 square foot (ft2)

Volume

liter (L) 0.2642 gallon (gal)

liter (L) 1.057 quart (qt)

liter (L) 61.02 cubic inch (in3

)

milliliter (mL) 0.06102 cubic inch (in3

)

cubic centimeter (cm3

) 0.06102 cubic inch (in3)

cubic meter (m3

) 264.2 gallon (gal)

cubic meter (m3

) 35.31 cubic foot (ft3)

Flow rate, velocity

milliliter per minute (mL/min) 0.06102 cubic inch per minute (in3

/min)

liter per minute (L/min) 0.2642 gallons per minute (gpm)

centimeter per day (cm/d) 0.0328 feet per day (ft/d)

meter per second (m/s) 283461 feet per day (ft/d)

Pressure

kilopascal (kPa) 0.1450 pound per square inch (psi)

kilopascal (kPa) 0.009869 atmosphere, standard (atm)

kilopascal (kPa) 0.3346 feet of water (at 39 degrees F)

kilopascal (kPa) 0.01 bar

Mass to weight force

gram (g) 0.0353 ounce (oz)

gram (g) 0.002205 pound (lb)

Velocity

knot (kn) 1.151 miles per hour (mph)

meter per second (m/s) 2.237 miles per hour (mph)

Discharge

cubic meters per second (m3

/s) 35.315 cubic feet per second (cfs)

liters per second (L/s) 0.03531 cubic feet per second (cfs)

Thermal conductivity

Watt per meter per degree Celsius 

(W/m/°C)

0.5778 BTU per foot-hour per degree 

Fahrenheit (BTU/ft-hr/°F)

Energy

Joule (J) 0.0009478 British thermal unit (BTU)

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

°F=(1.8×°C)+32

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

°C=(°F–32)/1.8
Introduction and Characteristics of Flow

By James W. LaBaugh and Donald O. Rosenberry

Chapter 1 of

Field Techniques for Estimating Water Fluxes Between 

Surface Water and Ground Water

Edited by Donald O. Rosenberry and James W. LaBaugh

Techniques and Methods Chapter 4–D2

U.S. Department of the Interior

U.S. Geological Survey
Contents

Introduction.....................................................................................................................................................5

Purpose and Scope .......................................................................................................................................6

Characteristics of Water Exchange Between Surface Water and Ground Water.............................7

Characteristics of Near-Shore Sediments .......................................................................................8

Temporal and Spatial Variability of Flow.........................................................................................10

Defining the Purpose for Measuring the Exchange of Water Between Surface Water 

and Ground Water..........................................................................................................................12

Determining Locations of Water Exchange....................................................................................12

Measuring Direction of Flow ............................................................................................................15

Measuring the Quantity of Flow .......................................................................................................15

Measuring Temporal Variations in Flow..........................................................................................15

Methods of Investigation............................................................................................................................16

Watershed-Scale Rainfall-Runoff Models......................................................................................16

Stream Discharge Measurements...................................................................................................17

Ground-Water Flow Modeling ..........................................................................................................17

Direct Measurement of Hydraulic Properties................................................................................20

Examination and Analysis of Aerial Infrared Photography and Imagery ..................................20

Dye and Tracer Tests..........................................................................................................................21

Thermal Profiling.................................................................................................................................26

Use of Specific-Conductance Probes.............................................................................................26

Electrical Resistivity Profiling ...........................................................................................................27

Hydraulic Potentiomanometer (Portable Wells) Measurements................................................27

Seepage Meter Measurements .......................................................................................................28

Biological Indicators ..........................................................................................................................28

References....................................................................................................................................................30

Figures

1. Summary of techniques that have been used for the measurement or estimation 

of water fluxes between surface water and ground water...................................................6

2. Typical hydraulic conditions in the vicinity of the shoreline of a surface-water body..............8

3. Decrease in seepage discharge with distance from shore ..................................................8

4. Generalized hydrologic landscapes ..........................................................................................9

5. Flow of salt tracer into a sandy lakebed, Perch Lake, Ontario ...........................................10

6. The length of the flow path and the direction of flow can vary seasonally and 

with distance from shore...........................................................................................................10

7. Example of ground-water exchange with Mirror Lake wherein lake water flows 

into ground water near shore, and ground water flows into the lake further from 

the shoreline................................................................................................................................11

8. Example of the effect of transpiration on the water table and the direction of 

water flux between surface water and ground water .........................................................12
9. Example of rise and fall of water-table mounds at the edge of surface-water 

bodies and changes in flow direction .....................................................................................13

10. Example of changes in flow direction related to onset and dissipation of a 

water-table mound adjacent to a river....................................................................................14

11. Example of flow interaction between surface water and ground water ..........................15

12. Fluvial-plain ground-water and stream-channel interactions showing channel 

cross sections .............................................................................................................................16

13. Example of the use of hydrographs to determine the amount of ground-water 

discharge to a stream................................................................................................................17

14. Example of the use of discharge measurements to determine surface-water/

ground-water interaction ..........................................................................................................18

15. Example of model grid used for simulation of surface-water/ground-water 

interaction....................................................................................................................................19

16. Example of shoreline segment definition for the calculation of water fluxes 

between surface water and ground water at a lake............................................................21

17. Example of use of thermal infrared imagery to delineate areas of discrete and 

diffuse ground-water discharge to surface water................................................................22

18. Example of the use of dye to examine water fluxes between surface water and 

ground water...............................................................................................................................23

19. Example of the use of a towed specific-conductance probe to identify groundwater discharge to surface waters .........................................................................................26

20. A, photograph of minipiezometer/hydraulic potentiomanometer in use; B, diagram

of hydraulic-potentiomanometer system...................................................................................27

21. Full-section view of seepage meter showing details of placement in the sediment..............28

22. Photographs of marsh marigold in Shingobee Lake, Minnesota........................................29

Introduction

Interest in the use and development of our Nation’s 

surface- and ground-water resources has increased significantly 

during the past 50 years (Alley and others, 1999; Hutson and 

others, 2004). At the same time, a variety of techniques and 

methods have been developed to examine and monitor these 

water resources. Quantifying the connection between surface 

water and ground water also has become more important 

because the use of one of these resources can have unintended 

consequences on the other (Committee on Hydrologic Science, 

National Research Council, 2004). In an attempt to convey the 

importance of the linkages and interfaces between surface water 

and ground water, the two have been described as a “single 

resource” (Winter and others, 1998). An improved understanding of the connection between surface and ground waters 

increasingly is viewed as a prerequisite to effectively managing these resources (Sophocleous, 2002). Thus, water-resource 

managers have begun to incorporate management strategies 

that require quantifying flow between surface water and ground 

water (Danskin, 1998; Bouwer and Maddock, 1997; Dokulil 

and others, 2000; Owen-Joyce and others, 2000; Barlow and 

Dickerman, 2001; Jacobs and Holway, 2004).

The use of surface water (or ground water) can change 

the location, rate, and direction of flow between surface 

water and ground water (Stromberg and others, 1996; 

Glennon, 2002; Galloway and others, 2003). Pumping wells 

in the vicinity of rivers commonly cause river water to flow 

into the underlying ground-water body, which can affect 

the quality of the ground water (Childress and others, 1991;

McCarthy and others, 1992; Lindgren and Landon, 1999; 

Steele and Verstraeten, 1999; Zarriello and Reis, 2000; Sheets 

and others, 2002). In some cases, ground water is pumped to 

provide water for cooling industrial equipment and then discharged into lakes, ponds, or rivers (Andrews and Anderson, 

1978; Hutson and others, 2004). Ground water also may be 

pumped specifically to maintain lake levels for recreation 

purposes, especially during droughts (Stewart and Hughes, 

1974; Mcleod, 1980; Belanger and Kirkner, 1994; Metz and 

Sacks, 2002). Surface water can be directed into surface basins 

where water percolates to the underlying aquifer—a process 

known as artificial recharge (Galloway and others, 2003). 

Ground-water discharge areas, where ground water flows into 

surface water, can be important habitats for fish (Garrett and 

others, 1998; Power and others, 1999; Malcolm and others, 

2003a, 2003b). Water in irrigation canals can flow or seep to 

an underlying aquifer, which eventually discharges water to 

rivers, thereby sustaining streamflow essential for the maintenance of fish populations (Konrad and others, 2003).

Interest in the interaction of surface water and ground 

water is not confined to inland waters. This interaction has 

been studied in coastal areas because fresh ground-water 

supplies can be affected by intrusion of saltwater (Barlow 

and Wild, 2002). Beyond the issue of water supply for human 

consumption, increased attention has been given to the ground 

water that discharges to oceans and estuaries, both in terms of 

water quantity and quality (Bokuniewicz, 1980; Moore, 1996, 

1999; Linderfelt and Turner, 2001). Discharge of fresh ground 

water to oceans and estuaries, also referred to as submarine 

ground-water discharge, is important in maintaining the flora 

and fauna that have evolved to exploit this source of fresh 

water in a saline environment (Johannes, 1980; Simmons, 

1992; Corbett and others, 1999). Nitrate in submarine groundwater discharge to estuaries and coastal waters can result in 

eutrophication of those waters (Johannes, 1980; Johannes and 

Hearn, 1985; Valiela and others, 1990; Taniguchi and others, 

2002). Withdrawals or pumping of ground water at near-shore, 

inland locations can reduce the submarine discharge of ground 

water offshore and change the environmental conditions of 

these settings (Simmons, 1992). Some coral reefs may be 

endangered by diminished submarine ground-water discharge 

(Bacchus, 2001, 2002).

The variety of settings of interest for the examination 

of the interaction between surface water and ground water 

makes evident the need for methods to describe and quantify 

that flow. The exact method chosen for each setting will vary 

depending on the physical and hydrological conditions present 

in those settings, as well as the scale of the interaction. Some 

degree of measurement uncertainty accompanies each method 

or technique. Thus, it is prudent to consider using more than 

one method to examine the interaction between surface water 

and ground water. Because numerous techniques and methods 

are available to describe and quantify the flow between surface 

water and ground water, it is useful to provide water-resource 

investigators an overview of available techniques and methods, 

as well as their application.

Chapter 1

Introduction and Characteristics of Flow

By James W. LaBaugh and Donald O. Rosenberry
6 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Purpose and Scope

Several methods have been developed and applied to the 

study of the exchange between surface water and ground water 

(fig. 1). Different methods are better suited for characterizing 

or measuring flow over large or small areas. If an initial view 

of a considerable area or distance is needed to determine where 

measurable ground-water discharge is occurring, aerial infrared photography or imagery can be effective reconnaissance 

tools. On a smaller scale, some methods may involve direct 

measurement of sediment temperature or specific conductance 

along transects within a surface-water body, or use of dyes or 

other tracers to indicate the direction and rate of water movement. The measurement of water levels in well networks in the 

watershed can be used to determine ground-water gradients 

relative to adjacent surface water, which in turn can indicate 

the direction and rate of flow between the surface-water body 

and the underlying aquifer. In streams and rivers, measurement of flow at the endpoints of a channel reach can reveal if 

the reach is gaining flow from ground water or losing flow to 

ground water. Addition of tracers to streams also can be used to 

determine surface-water interaction with ground water over a 

range of scales. Local interaction of surface water with ground 

Figure 1. Summary of techniques that have been used for the measurement or estimation of water fluxes between surface water 

and ground water. Techniques illustrated include: (A) aerial infrared photography and imagery, (B) thermal profiling, (C) the use of 

temperature and specific-conductance probes, (D) dyes and tracers, (E) hydraulic potentiomanometers, (F) seepage meters, (G) well 

networks, and (H) streamflow measurements. (Artwork by John M. Evans, U.S. Geological Survey, retired.)

A

B

C

D

D

F

F

E

E

G

G

H
Introduction and Characteristics of Flow 7

water is measured by placing devices such as thermistors, 

minipiezometers, and seepage meters in the sediment, to monitor temperature gradients, hydraulic gradients, or quantity of 

flow. Determination of how interaction of surface water with 

ground water changes over time is made possible by using datarecording devices (“data loggers”) in conjunction with pressure 

transducers, thermistors, and water-quality probes.

This report is designed to make the reader aware of 

the breadth of approaches (fig. 1) available for the study of 

the exchange between surface and ground water. To accomplish this, the report is divided into four chapters. Chapter 1 

describes many well-documented approaches for defining the 

flow between surface and ground waters. Subsequent chapters provide an in-depth presentation of particular methods. 

Chapter 2 focuses on three of the most commonly used 

methods to either calculate or directly measure flow of water 

between surface-water bodies and the ground-water domain: 

(1) measurement of water levels in well networks in combination with measurement of water level in nearby surface 

water to determine water-level gradients and flow; (2) use of 

portable piezometers (wells) or hydraulic potentiomanometers 

to measure hydraulic gradients; and (3) use of seepage meters 

to measure flow directly. Chapter 3 focuses on describing the 

techniques involved in conducting water-tracer tests using 

fluorescent dyes, a method commonly used in the hydrogeologic investigation and characterization of karst aquifers, and 

in the study of water fluxes in karst terranes. Chapter 4 focuses 

on heat as a tracer in hydrological investigations of the nearsurface environment.

This report focuses on measuring the flow of water 

across the interface between surface water and ground water, 

rather than the hydrogeological or geochemical processes that 

occur at or near this interface. The methods, however, that use 

hydrogeological and geochemical evidence to quantify water 

fluxes are described herein. This material is presented as a 

guide for those who have to examine the interaction of surface 

water and ground water. The intent here is that both the overview of the many available methods and the in-depth presentation of specific methods will enable the reader to choose those 

study approaches that will best meet the requirements of the 

environments and processes they are investigating, as well as 

to recognize the merits of using more than one approach. To 

that end, at this point it is useful to examine the content of 

each chapter in more detail.

Chapter 1 provides an overview of typical settings in 

the landscape where interactions between surface water 

and ground water occur. The chapter reviews the literature, 

particularly recent publications, and describes many welldocumented methods for defining the flow between surface 

and ground waters. A brief overview of the theory behind each 

method is provided. Information is presented about the field 

settings where the method has been applied successfully, and, 

where possible, generalizes the requirements of the physical 

setting necessary to the success of the method. Strengths and 

weaknesses of each method are noted, as appropriate. This 

will aid the investigator in choosing methods to apply to their 

setting. For those already familiar with some of these methods, the review of recent literature provides information about 

improvements in these methods.

Chapter 2 describes three of the most commonly used 

methods to either calculate or directly measure flow of water 

between surface-water bodies and the ground-water domain. 

The first method involves measurement of water levels in a 

network of wells in combination with measurement of the 

stage of the surface-water body to calculate gradients and 

then water flow. The second method involves the use of 

portable piezometers (wells) or hydraulic potentiomanometers 

to measure gradients. In the third method, seepage meters 

are used to directly measure flow across the sediment-water 

interface at the bottom of the surface-water body. Factors 

that affect measurement scale, accuracy, sources of error in 

using each of the methods, common problems and mistakes 

in applying the methods, and conditions under which each 

method is well- or ill-suited also are described.

Chapter 3 presents an overview of methods that are commonly used in the hydrogeologic investigation and characterization of karst aquifers and in the study of water fluxes in karst 

terranes. Special emphasis is given to describing the techniques 

involved in conducting water-tracer tests using fluorescent dyes. 

Dye-tracer test procedures described herein represent commonly 

accepted practices derived from a variety of published and 

previously unpublished sources. Methods that are commonly 

applied to the analysis of karst spring discharge (both flow and 

water chemistry) also are reviewed and summarized.

Chapter 4 reviews early work addressing heat as a tracer 

in hydrological investigations of the near-surface environment, 

describes recent advances in the field, and presents selected 

new results designed to identify the broad application of heat 

as a tracer to investigate surface-water/ground-water exchanges. 

An overview of field techniques for estimating water fluxes 

between surface water and ground water with heat is provided.

To familiarize readers with flow conditions that may 

occur during their studies, the next section of Chapter 1 

describes commonly observed interactions between surface 

water and ground water.

Characteristics of Water Exchange 

Between Surface Water and 

Ground Water

Most measurements made for the purpose of quantifying exchange between surface water and ground water are 

obtained at points within a short distance of the shoreline of 

the surface-water body. Shorelines represent the horizontal 

interface between ground water and surface water, an interface that is highly dynamic spatially and temporally. Because 

of the complex physical processes that occur in precisely the 

area where measurements are needed, it is important to understand those processes at shorelines and the range of potential 

changes in conditions at shorelines that occur over time. The 

following section elaborates these points.
8 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Typically, a significant break in slope in the water table 

occurs where the horizontal surface of a lake, stream, or wetland 

intersects the sloping surface of the ground-water table (fig. 2). 

Because of this break in slope, ground-water flow lines diverge 

where they extend beneath and end at the sediment-water interface. Diverging flow lines indicate that the rate of flow per unit 

area is decreasing. Given homogeneous and isotropic conditions 

in the porous media adjacent to and beneath the sediment-water 

interface, seepage across the interface will decrease exponentially with distance from shore (fig. 3) (McBride and Pfannkuch, 

1975; Pfannkuch and Winter, 1984). The movement of water 

between surface water and ground water can occur in a variety 

of settings or landscapes (fig. 4), each of which can be related 

to the break in slope of the water table defined by “an upland 

adjacent to a lowland separated by an intervening steeper slope” 

(Winter, 2001).

Ground-water flow lines bend substantially beneath 

the sediment-water interface just before they intersect the 

surface-water body. Measurements of hydraulic-head gradients 

typically assume that the flow lines either are horizontal (in 

the case of comparing heads in near-shore wells with surfacewater stage) or vertical (in the case of inserting the screened 

intervals of wells to some depth beneath the sediment-water 

interface). In reality, the orientation of the flow lines are somewhere between horizontal and vertical as shown in figure 5.

Characteristics of Near-Shore Sediments

Although some investigators have found that seepage 

decreases exponentially with distance from shore (Lee, 1977; 

Fellows and Brezonik, 1980; Erickson, 1981; Attanayake and 

Waller, 1988; Rosenberry, 1990), other studies report that the 

decrease in flow across the sediment-water interface is not 

exponential because of heterogeneity of the sediment. One of 

the early fndings of a departure from what would be expected 

in a homogeneous, isotropic setting was reported by Woessner 

and Sullivan (1984) in their study of Lake Mead, Nevada. At 

many of the transects across which they collected data in Lake 

Mead, they found seepage did not decrease exponentially, 

and furthermore, that seepage sometimes decreased and then 

increased with distance from shore. They reported a large variability in seepage with distance from shore. This variability 

was attributed to heterogeneity in the sediments in the vicinity 

of the sediment-water interface. Krabbenhoft and Anderson 

(1986) also reported that seepage was focused in a gravel lens 

that intersected the lakebed some distance from shore at Trout 

Lake, Wisconsin. It now generally is recognized that aquifers 

adjacent to and beneath surface-water bodies rarely can be 

considered homogeneous, and usually are not isotropic.

Many processes act to create heterogeneity at the sedimentwater interface. A few are listed below.

1. Fluvial processes—Depositional and erosional processes 

occur nearly constantly in streambeds and riverbeds, 

making heterogeneity a significant feature in these 

sediment-water interfaces. Organic deposits commonly 

are buried by deposition of inorganic material, resulting 

in interlayering of these different sediment types. Channel 

aggradation and flood scour can cause a shoreline to shift 

laterally many meters. Seasonal erosion and deposition 

related to spring floods also create a temporal component 

to the heterogeneity.

2. Edge effects—Shoreline erosion and deposition related 

to wave action in lakes, large wetlands, and rivers create 

heterogeneity at the sediment-water interface. Waves 

erode banks, which subsequently fail as new material 

slumps into the surface-water body. Fine-grained 

sediments are moved away from shore, often leaving a 

cobble- to boulder-sized pavement at the shoreline. Sediment deposition by overland flow commonly results in 

near-shore, fan-shaped deposits following heavy rainfall. 

Waves also rework sediments following slump events or 

sediment transport associated with overland flow, causing movement of fine-grained materials into voids created 

by movement of cobble- to boulder-sized sediments. In 

addition, changing surface-water stage causes the position 

A

Ground-water flow lines

b

m Break in

slope

Water-table well

Surface-water

body Shoreline segment

L

Flow passes beneath lake and is outside of local-flow domain

Land surface

Surface water Water table

Ground-water flow path

Figure 2. Typical hydraulic conditions in the vicinity of the 

shoreline of a surface-water body. (Artwork by Donald O. 

Rosenberry, U.S. Geological Survey.)

Figure 3. Decrease in seepage discharge with distance from 

shore (from Winter and others, 1998).
Introduction and Characteristics of Flow 9

MOUNTAIN

VALLEY

Direction of

ground-water flow

Water

table Water

table

Seepage

face

Break

in slope

Land surface

Direction of local

ground-water flow

Water

table

PLAYA

Land surface

Direction of regional

ground-water flow

Water

table

Direction of local

ground-water flow

PLATEAU AND HIGH PLAINS

Land surface

RIVERINE

VALLEY

Direction of regional

ground-water flow

Direction of local

ground-water flow

Regional upland

Water table Flood levels

COASTAL TERRAIN

Direction of regional

ground-water flow Direction of local

ground-water flow

Regional upland

Water table

Terrace

Ocean

Direction of regional

ground-water flow

Direction of local

ground-water flow

Water table

HUMMOCKY TERRAIN

A

B

C

D

E

F

Figure 4. Generalized hydrologic landscapes: A, narrow uplands and lowlands separated by a large steep valley side 

(mountainous terrain); B, large broad lowland separated from narrow uplands by steeper valley sides (playas and basins 

of interior drainage); C, small narrow lowlands separated from large broad uplands by steeper valley side (plateaus and 

high plains); D, small fundamental hydrologic landscape units nested within a large fundamental hydrologic landscape unit 

(large riverine valley with terraces); E, small fundamental hydrologic landscape units superimposed on a larger fundamental 

hydrologic landscape unit (coastal plain with terraces and scarps); F, small fundamental hydrologic landscape units 

superimposed at random on large fundamental hydrologic landscape units (hummocky glacial and dune terrain) (from 

Winter, 2001, copyright the American Water Resources Association, used with permission).

of the shoreline to change over time, resulting in lateral 

movement of all of the previously mentioned depositional and erosional processes that occur at the shoreline. 

Accumulation of organic debris, including buried logs and 

decayed plant matter, also contributes to heterogeneity as 

it is incorporated with the inorganic sediments, particularly on the downwind shores of surface-water bodies. In 

surface-water bodies that are ice covered during winter, 

ice rafting during fall and spring, when ice is forming or 

when the ice cover is melting, can substantially rework 

sediments at the downwind shoreline.

3. Biological processes—Benthic invertebrates constantly 

rework sediments, particularly organic sediments, as they 

carry out their life cycles. Bioturbation and bioirrigation 

are important processes for organic sediments in deeper 

water environments, but it can be significant in some nearshore settings also. Aquatic birds disturb the sediment 

as they search for benthic invertebrates, and fish rework 

sediments as they create spawning redds. Beavers and 

muskrats can make large-scale disturbances by removing considerable amounts of sediments for lodges and 

passageways, and the construction of dams.
10 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Temporal and Spatial Variability of Flow

Flow across the sediment-water interface commonly 

changes in direction and velocity temporally and spatially. 

Many occurrences of spatial and temporal variability in 

the exchange between surface water and ground water are 

described in the literature; a few examples are provided 

herein. Some of this variability is summarized in figure 6. In 

this illustration, water flows from the surface-water body to 

ground water through the bottom sediments located beyond a 

low-permeability layer some distance from shore. Yet closer 

to shore, ground water flows into the surface-water body. 

Finally, near the shore a depression in the water table created 

by evapotranspiration causes flow out of the lake. At the south 

shoreline of Mirror Lake, New Hampshire, water flows from 

the lake to ground water between the shoreline and approximately 8 meters from shore, and beyond that point, flow 

from ground water to the lake occurs (fig. 7) (Asbury, 1990; 

Rosenberry, 2005).

In many settings, evapotranspiration during the summer 

months can depress the water table adjacent to the shoreline 

of wetlands, streams, and lakes below the level of the surfacewater body (fig. 8) (Meyboom, 1966, 1967; Doss, 1993; 

Winter and Rosenberry, 1995; Rosenberry and others, 1999; 

Fraser and others, 2001). As a result, seasonal, and sometimes 

diurnal, reversals in flow between surface water and ground 

water may occur at the shoreline. The changes in direction of 

flow between surface water and ground water result from fluctuations in the amount of water removed from the water table 

because of evapotranspiration by plants along the margins of 

the surface-water body. On a seasonal basis, once evapotranspiration ceases to remove water from the near-shore regions, 

the near-shore depression in the water table dissipates, which 

then allows ground water to flow into the surface-water body. 

On a diurnal basis, more evaportranspiration in the day and 

less at night can cause the water table to fluctuate between 

levels below and above the adjacent surface-water level.

In many locations, water-table mounds can develop at 

the edge of surface-water bodies. Many studies have shown 

transient water-table mounds that form in response to precipitation or snowmelt (fig. 9) (see, for example, Winter, 

1986; Rosenberry and Winter, 1997; Lee and Swancar, 1997). 

Most of these water-table mounds were of short duration and 

formed in response to large rainfall events. Reversals of flow 

of longer duration also occur at some settings. Jaquet (1976) 

reported a reversal of flow along part of the shoreline at Snake 

Lake, Wisconsin, following spring thaw and considerable 

rainfall (19 centimeters) over a 5-week period that persisted 

for several months.

0 1 METER

0 2 4 FEET

ML39 ML36

73

ML29

ML29 - multi-level well

43 23

ML34

ML19 ML7

ML9 ML10

ML15

3

10

INJECTION WELLS

ML26

SM21 SM20

ML37

SM6

SM6 - seepage meter

SM19

ML8

C' C

SM3

Figure 5. Flow of salt tracer into a sandy lakebed, Perch Lake, Ontario. Numbers in 

shaded areas (representing center of mass of salt plume) are the days following salt 

injection (modified from Lee and others, 1980, copyright 1980 by the American Society 

of Limnology and Oceanography, Inc., used with permission).

Figure 6. The length of the flow path and the direction of flow 

can vary seasonally and with distance from shore. (Artwork by 

Donald O. Rosenberry, U.S. Geological Survey.)

Land surface

Low-permeability layer

Surface-water

body
Introduction and Characteristics of Flow 11

Outlet

93

0 2 METERS

0 2 4 6 8 FEET

Mirror

Lake

B

Hubbard Brook

Study

site

235

230

225

220

215 213.3

213.2

210.9

207.9

Shoreline

Seepage rates,

in centimeters/day

ALTITUDE, IN METERS ABOVE SEA LEVEL

260

250

240

230

220

210

200

190

180

170

160

150

A

B

235

230

225

220

214

215

207.9

210.9

213.3

213.2

NEW HAMPSHIRE

72°

44°

0

0

300 600 METERS

1200600 1800 2400 FEET

N

Study site

Study site

Crystalline bedrock

Glacial drift

Line of equal

hydraulic head

(dashed where interval

is variable)

Water table

Piezometer point

Mirror Lake 213.36 meters

Water-table well

Hubbard

Brook

–2

+3 +0.3

–0.6

–11

–12

–0.4

–2 –3

–0.6

–29

–23

–85

+4

–20

–54 –153

–120

–4

–6

Well

Direction of

ground-water flow

214

Lake sediments 212.1 212.1

Direction of

ground-water flow

A

Study

site

Transect line

Figure 7. Example of ground-water exchange with Mirror Lake wherein lake water flows into ground water near 

shore (shown by negative numbers), and ground water flows into the lake farther from the shoreline (shown by 

positive numbers). (Modified from Rosenberry, 2005, copyright 2005 by the American Society of Limnology and 

Oceanography, Inc., used with permission.)
12 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Ground-water levels adjacent to streams also fluctuate 

in response to the rise and fall of water in the stream (Winter, 

1999). An example of the resulting changes in flow direction between a stream and ground water is illustrated by data 

from the Cedar River in Iowa (fig. 10). In flowing waters, 

movement of surface water into the subsurface and out again 

occurs both at the bottom of the stream channel and beneath 

upland areas between bends in the open channel (fig. 11). This 

transient flow of surface water into and out of the subsurface is 

also known as hyporheic flow (Orghidan, 1959). Ground water 

flowing toward a surface-water body may discharge directly 

into that body or mix with hyporheic flow prior to emerging 

into open-water flow. The various interactions with ground 

water include situations in which flow is parallel to the stream 

(fig. 12) and does not intersect the surface water (Woessner, 

1998, 2000).

Defining the Purpose for Measuring 

the Exchange of Water Between 

Surface Water and Ground Water

Water-resource investigators and water-resource managers have many reasons to quantify the flow between surface 

water and ground water. Perhaps the most common reasons 

include: calculating hydrological and chemical budgets of 

surface-water bodies, collecting calibration data for watershed 

or ground-water models, locating contaminant plumes, locating areas of surface-water discharge to ground water, improving their understanding of processes at the interface between 

surface water and ground water, and determining the relation 

of water exchange between surface water and ground water 

to aquatic habitat. For many investigations, it is sufficient to 

make a qualitative determination regarding the direction and 

relative magnitude of flow, either into or out of the surfacewater body.

Methods for quantifying flows should be selected to be 

appropriate for the scale of the study. For a watershed-scale 

study in which multiple basins may be involved, small-scale 

flow phenomena, such as near-shore depressions in the 

water table or spatial variability of flux related to geologic 

variability, likely are of little importance to the overall study 

goal. In such watershed-scale studies, the net flux integrated 

over an entire stream reach, or lake, or wetland often is the 

desired result. Watershed-scale flow modeling, ground-water 

flow modeling, flow-net analysis, or dye- and geochemicaltracer tests, often are used in such large-scale studies, studies 

on the order of hundreds of meters or a kilometer or more in 

length or breadth.

If the goal of a study is to identify and (or) delineate 

zones or areas of flow of surface water to ground water, or 

flow of ground water to surface water, smaller scale spatial 

and temporal variations in flow become important, and measurement tools that provide results over an intermediate scale, 

many tens to hundreds of meters should be selected. In many 

instances, measurement of surface-water flow at two places 

some distance apart in a segment of stream, which enables 

calculation of gains or losses in flow in the segment, is appropriate for these types of studies. For local, small-scale studies in which flow to or from surface water may be focused, 

small-scale tools such as seepage meters, small portable wells 

(“minipiezometers” or hydraulic potentiomanometers), and 

buried temperature probes may be most appropriate. Devices 

designed to measure flow in a small area are known as seepage meters because the term seep refers to “a small area 

where water moves slowly to the land surface” (USGS Water 

Basics Glossary http://capp.water.usgs.gov/GIP/h2o_gloss/). 

Seepage is defined as “the slow movement of water 

through small cracks, pores, interstices, and so forth, 

of a material into or out of a body of surface or subsurface water” (USGS Water Science Glossary of Terms 

http://ga.water.usgs.gov/edu/dictionary.html#S).

Once the water-resource investigator has decided on 

the purpose of the study and the scale of the investigation, 

methods of investigation can be chosen to most effectively 

determine where an exchange between surface water and 

ground water is taking place, the direction of flow, the rate 

or quantity of that flow, and whether the rate and direction 

of flow changes over time.

Determining Locations of Water Exchange

The investigator who wishes to determine where water 

exchange is taking place between surface water and ground 

water has many options, particularly in the case of groundwater discharge to surface water. Reconnaissance tools useful 

over larger areas, such as dye-tracer tests, aerial photography and imagery, temperature and specific-conductance 

probes, and surface-water discharge measurements, can be 

supplemented by reconnaissance tools useful in smaller areas 

of interest, such as seepage meters, minipiezometers, and 

biological indicators.

Surface

water

Transpiration

Land surface

Water table during

growing season

Water table during

dormant season

Figure 8. Example of the effect of transpiration on the water 

table and the direction of water flux between surface water and 

ground water (from Winter and others, 1998).
Introduction and Characteristics of Flow 13

Figure 9. Example of rise and fall of water-table mounds at the edge of surfacewater bodies and changes in flow direction (from Lee and Swancar, 1997). A, Vertical 

distribution of head showing downward head gradient conditions, August 6, 1985. 

B, Vertical distribution of head during high water-level conditions, October 17, 1985.

119.68 1PN-22

1PN-65

1PN-50

1PN-35

1PN-20

119.48

125.60

125.67

125.73

1 127.24 128.09

127.66

2PN-9

2PN-20 125.96

2PN-35

125.23

2PN-50

No data

A

B

WT - 15

2PN

Midlake

Lake Lucerne

Pivot

point

1

125.11

180

160

140

120

100

80

60

40

20

Sea

level

20

40

0 250 500 750 1,000 1,250 1,500 1,750 2,000 2,250 2,500 2,750 3,000 3,250

ALTITUDE, IN FEET, ABOVE OR BELOW SEA LEVEL

DISTANCE, IN FEET, FROM WELL WT-15 ALONG PART OF TRANSECT B–B’

VERTICAL SCALE GREATLY EXAGGERATED

EXPLANATION

125 Equipotential line—Interval 1 foot.

 Datum is sea level

Direction of ground-water flow

Well and number

Head—In feet above sea level

Water table

1

Value for 8/8/85 119.54

1PN-155

119.48 125.77

2PN-130

1PN-7

124.90

1PN

WT - 17

EXPLANATION

Equipotential line—Interval 1 foot.

 Datum is sea level

Direction of ground-water flow

Well and number

Head—In feet above sea level

Water table

121

128.14

2PN-35

120.61

2PN-130

180

160

140

120

100

80

60

40

20

Sea

Level

20

0 250 500 750 1,000 1,250 1,500 1,750 2,000 2,250 2,500 2,750 3,000 3,250

40

ALTITUDE, IN FEET, ABOVE OR BELOW SEA LEVEL

DISTANCE, IN FEET, FROM WELL WT-15 ALONG PART OF TRANSECT B–B’

VERTICAL SCALE GREATLY EXAGGERATED

120.23

1PN-155

120.34 1PN-72

121.46

127.12 1PN-50

127.19 1PN-35

127.25

1PN-20

1PN-7

128.37

130.02

125.96

125.70

Midlake 2PN-35

128.14

2PN-20

127.50

2PN-9

127.37 129.88 WT-15

2PN

Pivotpoint

Midlake

Lake Lucerne

1PN

WT-17

2PN-50

127.45

B B'

B B'

125

124

123

122

121

120

126

127

127

126

1PN-7

125.77

1PN-65

128

129

130

127

126

124

125

123

126

128

127

129

121

122
14 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 10. Example of changes in flow direction related to onset and dissipation of a water-table mound adjacent to a river (from Squillace 

and others, 1993, used in accordance with usage permissions of the American Geophysical Union wherein all authors are U.S. Government 

employees). Hydrogeologic sections for part of the Cedar River, Iowa, for three periods in 1990. A, Movement of ground water into the river 

prior to a period of high river stage. B, Movement of river water into the contiguous aquifer during high river stage. C, Return of some of the 

water from the aquifer during declining river stage.

210

208

206

204

202

200

198

196

194

192

210

208

206

204

202

200

198

196

194

192

210

208

206

204

202

200

198

196

194

192

ALTITUDE, IN METERS

0.1

EXPLANATION

Fine- to coarse-grained

 sand

Till

Fine- to coarse-grained

 silty/clayey sand

Line of equal atrazine concentration, 

 in micrograms per liter

Concentration of atrazine in river at 

 time of sampling, in micrograms 

 per liter

Well location

Direction of ground-water flow

Cedar

River

(0.21)*

0.5

0.5

0.5

Cedar

River

(0.12)*

Cedar

River

(0.51)*

Sampling period February 20–22

Sampling period March 20–22

Sampling period April 3–5

Water

table

Geologic

boundary

Water

table

Geologic

boundary

Water

table

Geologic

boundary

(X.XX)*

Vertical Exaggeration × 4

Datum is sea level

0.4

0.3

0.2

0.1

0.3

0.1

0.2

0.2

0.3

0.3

0.1

0.3 0.6

0.2 0.6 0.5

0.4

0.5

0.3

0.1

0.6 0.5

0.4

0.5

0.2

0.1

0.3

0.2

0.2

0.3

0.3

0.4

0.3

0.2

0.1

0.2

A

B

C

0

0 100 200 FEET

20 40 60 METERS
Introduction and Characteristics of Flow 15

Measuring Direction of Flow

Comparison of surface-water levels and adjacent groundwater levels indicates direction of flow. If the surface-water 

level is higher than adjacent ground-water levels, the direction of flow is from the surface water to ground water. If the 

opposite is the case—ground-water levels are higher than 

nearby surface-water levels—then the direction of flow is from 

ground water to surface water. In addition to indicating the 

direction of flow, water-level measurements provide information about the magnitude of the hydraulic gradients between 

surface water and ground water. In some instances, however, 

these gradients can be altered locally. For example, vegetation 

between the wells and the edge of the surface-water body can 

transpire sufficient water to cause a local depression in the 

water table close to the edge of the surface water (Meyboom, 

1966, 1967; Doss, 1993; Rosenberry and Winter, 1997; Fraser 

and others, 2001). Thus, it can be important to measure 

the direction of flow at a local scale using portable wells, 

minipiezometers, or hydraulic potentiomanometers.

Another way to determine if a section of stream or river 

is receiving ground-water discharge or is losing water to the 

underlying aquifer is by measurement of surface-water flow at 

two places some distance apart in a reach of stream, a practice 

commonly known as a “seepage run” (Harvey and Wagner, 

2000). If the amount of flow in the stream has increased over 

the reach, the increase may be attributed to ground-water 

discharge to the stream. If flow in the selected reach of stream 

has decreased, the decrease may be attributed to surface 

water flowing into ground water. It is important to recognize, 

however, that the direction of flow indicated by any change 

in streamflow is a “net direction” over the selected reach, 

and that within the reach, water may be moving into and out 

of the stream (and conversely, into and out of the underlying 

aquifer). It is important to account for any inflows or outflows 

within the stream reach, such as diversions for irrigation or 

channelized return flows from fields.

Measuring the Quantity of Flow

The volume of water flowing between surface water 

and ground water, either as surface water into ground water 

or ground water into surface water, can be measured directly 

with seepage meters. Measurement of changes in water 

temperatures over time at a specific site above the sediment, 

at the sediment-water interface, and within the sediment 

makes possible the determination of the amount of water 

exchange occurring between surface water and ground water. 

The exchange of water between surface water and ground 

water also can be examined and estimated by using dye 

tracer tests or by using other tracers. Such dyes or tracers are 

added directly to a stream and then their concentrations are 

measured at some point or points downstream. Changes in 

the concentration of the dye or other tracer over time downstream from where they are injected enables calculation of 

ground-water inputs.

Measuring Temporal Variations in Flow

In many instances, the rate of exchange between 

surface water and ground water varies over time scales 

of hours, days, or months. The direction of flow also may 

reverse on a seasonal basis or temporarily during a flood, for 

example. Measuring temporal variation in the rate of water 

exchange requires multiple measurements over these time 

periods. Measuring devices equipped with data recorders 

(“data loggers”) enable the investigator to record repeated 

measurements at specified time intervals to document 

temporal changes.

Gravel bar

Gravel bar

Sand and gravel

Bank

Bank Gravel bar

Stream

Water surface

A. View from Above

B. Sectional View

Sand and gravel

Till

Figure 11. Example of flow interaction between surface water 

and ground water (from Dumouchelle, 2001). Schematic of flow in 

Chapman Creek, west-central Ohio. (Arrows indicate direction of 

flow. Diagrams not to scale.)
16 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Methods of Investigation

Common methods to examine exchange of water between 

surface-water bodies and ground-water bodies are described 

below. Some of these methods make use of already installed 

hydrological instruments and existing data, rather than requiring the investigator to make measurements of hydrologic characteristics. When using such methods, however, the investigator may install wells, stream-gaging equipment, or rain gages, 

as needed, to obtain sufficient data to make the application of 

methods possible and the results less uncertain. Other methods 

require that the investigator make additional, specific measurements or observations of hydrological, physical, chemical, or 

biological characteristics.

Watershed-Scale Rainfall-Runoff Models

Many analytical and numerical models that relate precipitation, ground-water recharge, and ground-water discharge to 

temporal variability of flow in a stream have been developed. 

A fundamental assumption in these models is that streamflow is an integrated response to these processes over the 

stream’s watershed, and that ground-water discharge to the 

stream provides the steady flow in the stream between rainfall 

events, commonly referred to as baseflow. Analytical models 

generally determine baseflow through hydrograph separation 

techniques. Several automated routines have been developed 

to assist in this determination (Rutledge, 1992; Rutledge, 

1998) (fig. 13). Other analytical methods also have been used 

to quantify the interaction between ground water and surface 

water, including an analytic-element method (Mitchell-Bruker 

and Haitjema, 1996) and a nonparametric regression model 

(Adamowski and Feluch, 1991).

Several numerical models commonly referred to as 

rainfall-runoff models have been developed; these models areally divide watersheds and subwatersheds and calculate hydrologic parameters for each smaller area (for example, Federer 

and Lash, 1978; Leavesley and others, 1983, 1996, 2002; Beven 

and others, 1984; Beven, 1997; Buchtele and others, 1998). 

Rainfall-runoff models generally are calibrated to match river 

flow at the outlet of a watershed or subwatershed. Some models 

include the ground-water component of flow in each area. The 

current trend is to couple distributed-area watershed-scale models with ground-water flow models in order to better determine 

the temporal and spatial variability of the interaction between 

ground water and surface water (for example, Leavesley and 

Hay, 1998; Beven and Feyen, 2002).

Figure 12. Fluvial-plain ground-water and stream-channel interactions showing channel cross 

sections classified as: A, gaining; B and C, losing; D, zero exchange; and E, flow-through. The 

stream is dark blue. The water table and stream stage (thicker lines), ground-water flow (arrows), 

and equipotential lines (dashed) are shown (from Woessner, 1998, copyright American Institute of 

Hydrology, used with permission).

B D

E

A C
Introduction and Characteristics of Flow 17

Stream Discharge Measurements

Measurements of stream discharge (Rantz and others, 

1982a, b; Oberg and others, 2005) made as part of seepage runs 

(described earlier) can be used to determine the occurrence and 

rate of exchange of water between surface water and ground 

water in streams and rivers (fig. 14). The results of seepage runs 

have been used to provide an integrated value for flow between 

a stream and ground water along a specific stream reach. This 

method works well in small streams, but for larger streams and 

rivers, the errors associated with the measurement of flow in 

the channel often are greater than the net exchange of water to 

or from the stream or river. This method also requires that any 

tributaries that discharge to a stream along the reach of interest 

be measured and subtracted from the downstream discharge 

measurement. Likewise, withdrawals from the stream, such as 

that for irrigation, must be measured and added to the downstream discharge measurement.

The application of seepage-run data, however, is limited 

by the ratio of the net flow of water to or from the stream 

along a stream reach to the flow of water in the stream. The 

net exchange of water across the streambed must be greater 

than the cumulative errors in streamflow measurements. For 

example, if the errors in the stream discharge measurements 

are 5 percent of the true, actual flow, then according to the 

rules of error propagation, in order to be able to detect the net 

flow of water to or from the stream along the reach of interest, the value of net flow must be greater than 7 percent of 

the streamflow. Despite these limitations, many hydrologic 

studies have made use of this method with good results [for 

example, Ramapo River, New Jersey−Hill and others (1992); 

Bear River, Idaho and Utah−Herbert and Thomas (1992); 

Souhegan River, New Hampshire−Harte and others (1997); 

Lemhi River, Idaho−Donato (1998); constructed stream 

channel Baden-Württemberg, Germany−Kaleris (1998)]. The 

information gained from seepage runs can be enhanced with 

data obtained by using other techniques such as minipiezometers, seepage meters, temperature and specific-conductance 

measurements to better define surface-water/ground-water 

fluxes [for example, creeks and rivers in the Puget Sound area 

of Washington–Simonds and others (2004); and Chapman 

Creek, Ohio–Dumouchelle (2001)]. Seepage-run results also 

can provide estimates of hydraulic conductivity of the streambed on a scale appropriate for ground-water flow modeling 

(Hill and others, 1992).

Ground-Water Flow Modeling

Since 1983, most investigators who have used the numerical modeling approach in the quantification of flows between 

surface water and ground water have used the U.S. Geological 

Survey MODFLOW modular modeling code (Harbaugh and 

others, 2000). This finite-difference model contains an original 

“river package” that can simulate flows to or from a river, 

assuming the river stage does not change during a specified 

time period (referred to as a stress period in MODFLOW), but 

can change from one time period to the next. Several other 

MODFLOW modules or packages also have been developed 

to simulate fluxes between surface water and ground water. 

These include streamflow routing packages (Prudic, 1989; 

60 70 80 90

60 70 80 90

1

10

100

1,000

10,000

FLOW, IN CUBIC FEET PER SECOND

TIME, IN DAYS

1

10

100

1,000

10,000

FLOW, IN CUBIC FEET PER SECOND

TIME, IN DAYS

Streamflow

Pulse

Streamflow

Pulse

A

B

Figure 13. Example of the use of hydrographs to determine the 

amount of ground-water discharge to a stream (from Rutledge, 

2000). Hydrographs of streamflow for Big Hill Creek near 

Cherryvale, Kansas, for March 1974 (blue circles and dashed 

line), and hydrograph of estimated ground-water discharge using 

the PULSE model (red line). (Note: In each example, the total 

recharge modeled is 0.73 inch, which is the same as the total 

recharge estimated from RORA [a recession-curve-displacement 

method for estimating recharge] for this period. In example A, 

recharge is modeled as 0.65 inch on day 69 and 0.08 inch on day 

74. In example B, recharge is modeled as a gradual process that is 

constant from day 68 to day 72).
18 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

0 2 4 6 8 MILES

0 2 4 6 8 KILOMETERS

EXPLANATION

Seepage run reach and 

 identification number

Gaging station—Records

 kept by U.S. Geological

 Survey (USGS) or Bureau

 of Reclamation (BOR)

Other discharge measurement 

 site

Arbitrary boundary between 

 upper and lower Lemhi 

 River Basin

14

113°40'

113°50'

45°10' 45°10'

113°30'

BOR gaging station

at L-1 diversion

BOR gaging station

at L-3a diversion

BOR gaging station

at Barracks Lane

USGS gaging station below

L-5 diversion near Salmon

11 10

12

13

14

Lemhi 

 

 

 River

45°00'

8

9

USGS gaging

station near

Lemhi

Tendoy

45°00'

LOWER

BASIN

45°50'

3

4

5

6

Lemhi

113°30'

44°50'

1

2

44°40'

113°50'

113°40'

44°30'

113°30'

113°20' 113°10'

113°00'

44°30'

44°40'

113°10'

UPPER

BASIN

BOR gaging station

at Leadore

7

BOR gaging station at

Bureau of Land Management

McFarland Campground

Leadore

Salmon

Figure 14. Example of the use of discharge measurements to determine surface-water/ground-water interaction 

(from Donato, 1998). Seepage run reaches, gaging stations, and discharge measurement sites in the Lemhi River 

Basin, east-central Idaho, August and October 1997.
Introduction and Characteristics of Flow 19

13,000 FEET

50 FEET

LAYER

13,000 FEET

a

b

? ?

1

2

3

4

5

A

B

PLAN VIEW

CROSS-SECTIONAL VIEW

Figure 15. Example of model grid used for simulation of surface-water/ground-water interaction (from Merritt and Konikow, 2000). 

The lateral and vertical grid discretization for test simulation 1: A, Plan view—Shaded area is the surface extent of lake cells in layer 1. 

Interior grid dimensions are 500 and 1,000 meters. Border row/column cells are 250 feet thick. The locations of hypothetical observations 

wells are denoted by a and b. B, Cross-sectional view—Shaded area is the cross section of the lake. Although a nominal 10-foot 

thickness is shown for layer 1, the upper surface of layer 1 is not actually specified, and lake stages and aquifer water-table altitudes 

may rise higher than the nominal surface shown above.
20 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Prudic and others, 2004), a reservoir package (Fenske and 

others, 1996), a lake package (Cheng and Anderson, 1993), 

and more recently, a more elaborate lake package (Merritt and 

Konikow, 2000) (fig. 15). More advanced MODFLOW-based 

programs have been developed to couple one-dimensional, 

unsteady streamflow routing with MODFLOW (Jobson and 

Harbaugh, 1999; Swain and Wexler, 1996). Advances also 

are being made in coupling MODFLOW with watershed 

models that simulate many of the surface-water processes 

within a basin (Sophocleous and others, 1999; Sophocleous 

and Perkins, 2000; Niswonger and others, 2006). One of 

the most challenging aspects of coupling ground-water and 

surface-water models has been representation of flow through 

the unsaturated zone beneath a stream. Two new programs 

have recently been developed for MODFLOW to simulate 

one-dimensional (Niswonger and Prudic, 2005) and threedimensional (Thoms and others, 2006) flow in the unsaturated 

zone. Many of these packages require a determination of the 

transmissivity of the sediments at the interface between the 

aquifer and the surface-water body. Transmissivity is determined by multiplying hydraulic conductivity by the thickness 

of the lakebed or riverbed sediments.

Direct Measurement of Hydraulic Properties

The relation between the stage of a surface-water body and 

the hydraulic head measured in one or more nearby water-table 

wells can be used to calculate flows of water between surface 

water and ground water [Williams Lake, Minnesota−LaBaugh 

and others (1995); Vandercook Lake, Wisconsin−Wentz and 

others (1995); large saline lakes in central Asia−Zekster (1996); 

Lake Lucerne, Florida−Lee and Swancar (1997); Waquoit Bay, 

Cape Cod, Massachusetts−Cambareri and Eichner (1998); Otter 

Tail River, Minnesota–Puckett and others (2002)]. The Darcy 

equation (eq. 1) is used to calculate flow between ground water 

and surface water along specific segments of shoreline.

Q KA h h

L  1 2 
 , (1)

where

Q is flow through a vertical plane that extends 

beneath the shoreline of a surface-water 

body (L3

/T),

A is the area of the plane through which all 

water must pass to either originate from 

the surface-water body or end up in the 

surface-water body, depending on the 

direction of flow (L2

),

K is horizontal hydraulic conductivity (L/T),

h1 is hydraulic head at the upgradient well (L),

h2 is hydraulic head at the shoreline of the 

surface-water body (L),

and

L is distance from the well to the shoreline (L).

Shoreline segments are delineated/selected on the assumption 

that the gradient between a nearby well and the surface-water 

body, the hydraulic conductivity of the sediments, and the 

cross-sectional area through which water flows to enter or 

leave the lake, are uniform along the entire segment (fig. 16). 

Flows through each segment are summed for the entire 

surface-water body to compute net flow. The scale of the 

shoreline segments, and the scale of the study, depend on the 

scale of the physical setting of interest and the density of monitoring wells. Further detail regarding this method is provided 

in Chapter 2, in the section “Wells and Flow-Net Analysis.”

Examination and Analysis of Aerial Infrared 

Photography and Imagery

Aerial infrared photography and imagery have been 

used to locate areas of ground-water discharge to surface 

waters (Robinove, 1965; Fischer and others, 1966; Robinove 

and Anderson, 1969; Taylor and Stingelin, 1969). This technique is effective only if the temperatures of surface water and 

ground water are appreciably different. Information obtained 

from infrared scanners can be captured electronically or 

transferred to film, on which tonal differences correspond to 

differences in temperature (Robinove and Anderson, 1969; 

Banks and others, 1996) (fig. 17). Published studies indicate 

tonal differences corresponding to a difference in temperature of approximately 2 degrees Celsius are distinguishable 

(Pluhowski, 1972; Rundquist and others, 1985; Banks and 

others, 1996).

Within the limits of the ability of infrared imagery to 

distinguish temperature differences between surface water 

and ground water, the inspection of such imagery enables 

more rapid identification of gaining reaches in streams over 

large areas than can be accomplished by stream surveys that 

measure temperature directly (Pluhowski, 1972). Another 

advantage of this method in identifying areas of ground-water 

discharge to surface-water bodies is its application where 

using other techniques such as dye tracing or direct temperature measurements are impractical, or access on the ground is 

difficult (Campbell and Keith, 2001) or dangerous (Banks and 

others, 1996).

Using thermal-infrared imagery to distinguish zones of 

ground-water discharge is practical for locating diffuse and 

focused ground-water discharge (Banks and others, 1996). 

This capability has been demonstrated in a variety of environments. Examples for lakes are Crescent Lake, Nebraska 

(Rundquist and others, 1985), where the flow is diffuse and 

occurs over a large area, and Great Salt Lake and Utah Lake 

in Utah (Baskin, 1998), where the ground-water flow into 

the lake is focused at springs. Campbell and Keith (2001) 

found the technique useful in locating many springs flowing 

into streams and reservoirs in northern Alabama. Examples 

for estuaries are creeks flowing into Chesapeake Bay, 

Maryland, and the shorelines of the Gunpowder River and the 

Chesapeake Bay into which the river flows (Banks and others, 
Introduction and Characteristics of Flow 21

1996), as well as creeks and rivers flowing into Long Island 

Sound, New York (Pluhowski, 1972). Examples of the use 

of infrared imagery to detect areas of ground-water discharge 

to marine waters include the delineation of areas of diffuse 

ground-water flow into Long Island Sound (Pluhowski, 1972) 

and focused ground-water flow as springs to the ocean, such 

as around the perimeter of the island of Hawaii (Fischer and 

others, 1966).

Dye and Tracer Tests

Dyes and other soluble tracers can be added to water 

and then “tracked” to provide direct, qualitative information 

about ground-water movement to streams. Fluorescent dyes 

that are readily detected at small concentrations and pose little 

environmental risk make a useful tool for tracing ground-water 

flow paths, particularly in karst terrane (Aley and Fletcher, 

1976; Smart and Laidlaw, 1977; Jones, 1984; Mull and others, 

1988). Thus, dye-tracer studies can be used to determine the 

time-of-travel for ground water to move to and into surface 

water, as well as hydraulic properties of aquifer systems (Mull 

and others, 1988). The use of dyes as tracers is described in 

more detail in Chapter 3. Commonly, a reconnaissance of the 

ground-water basin is made to identify likely areas of potential 

surface-water flow into ground water or ground-water flow 

to the surface. An inventory is made of springs, sinkholes, 

boreholes or screened wells, and sinking streams. Appropriate 

sites then are picked for dye injection, and the potential discharge areas, springs, and stream reaches are monitored over 

an appropriate period of time, hours or days, for appearance of 

the dye (fig. 18).

Solute tracers have been used to aid in the determination of water gains or losses within the channel of a stream or 

river (Kilpatrick and Cobb, 1985). This technique is known as 

dilution-gaging. A variety of tracers have been used in such 

studies, either alone or in combination, usually including a 

Figure 16. Example of shoreline segment definition for the calculation of water fluxes between surface 

water and ground water at a lake (modified from LaBaugh and others, 1995, used in accordance with author 

rights of the National Research Council of Canada Press). Location of wells and shoreline segments used to 

calculate flow between surface water and ground water at Williams Lake, Minnesota.

47°00'

95°00'

M I N N E S O T A

Williams Lake

Williams

Lake 31

8

25

24

6

4 7

1

Mary

Lake

EXPLANATION

Well location and

 number

Area of inseepage

Area of outseepage

8

I3

04

04

05

03

02

I3

I2

I1

01

0 300 600 900 1200 FEET

0 100 200 300 METERS
22 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 17. Example of use of thermal infrared imagery to delineate areas of discrete and diffuse ground-water discharge to surface 

water (from Banks and others, 1996, reprinted from Ground Water with permission from the National Ground Water Association, 

copyright 1996, thermal imagery of O-Field study area, Aberdeen Proving Ground, Maryland).
Introduction and Characteristics of Flow 23

Figure 18. Example of the use of dye to examine water fluxes between surface water and ground water (from Carter 

and others, 2002). Dye testing has been done in Boxelder Creek, South Dakota, which can lose as much as 50 cubic 

feet per second of flow to the bedrock aquifers. In the upper left photograph, nontoxic, red dye is poured into Boxelder 

Creek upstream from a major loss zone. In the upper right photograph, dye in the stream can be seen disappearing 

into a sinkhole in the Madison Limestone. In the bottom photograph, dye in the stream emerges downstream at Gravel 

Spring, which is about 671 meters (2,200 feet) (linear distance) from the major loss zone. The length of time for the first 

arrival of dye to travel this distance is variable depending on flow conditions but generally is about 1 to 2 hours (Strobel 

and others, 2000). Thus, the ground-water velocity is about 0.3 to 0.6 kilometer per hour (0.2 to 0.4 mile per hour), 

which is a very fast rate for ground water. Dye also has been recovered at City Springs, which is in the Rapid Creek 

Basin, about 30 days after injection. This demonstrates that ground-water flow paths are not necessarily restricted 

by surface-water drainage basins. (Photographs by Derric L. Isles, South Dakota Department of Environment and 

Natural Resources.)
24 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

tracer expected to be nonreactive in the waters of the stream to 

which it is added, such as lithium (for example, in the Snake 

River, Colorado–Bencala and others, 1990) or chloride (for 

example, Chalk Creek, Colorado−Kimball, 1997). In this 

technique, a known quantity of solute is added at a specified 

rate for a short interval of time at the upstream cross section 

of the stream segment of interest, and concentrations of the 

solute are measured at one or more points downstream over 

time. Discharge is calculated from the amount of dilution that 

occurs at the downstream point or points. Kimball (1997) 

indicated that Qs

 (the discharge in the stream) is calculated 

as follows:

Qs = (CiQi) / (CB – CA) (2)

where

Ci is the tracer concentration in the injection 

solution,

Qi is the rate of injection into the stream,

CB is the tracer concentration downstream,

and

CA is the tracer concentration upstream from the 

injection point.

When coupled with stream-segment discharge measurements, 

use of solute tracers also enables calculation of the rates of 

ground-water inflow and outflow within a stream segment 

(Harvey and Wagner, 2000). At the same time the solute is 

injected and monitored within the stream segment, physical 

velocity measurements (streamflow) are made at the upstream 

and downstream sections of the stream reach. The streamflow 

measurements provide information on whether or not there 

was a net loss or gain of flow within the reach due to interaction with ground water. Harvey and Wagner (2000) indicate 

the solute tracer, or dilution-gaging, values determine groundwater inflow. Thus, ground-water outflow can be calculated by 

subtracting the net loss or gain from the solute tracer-derived 

ground-water inflow value.

Calculation of chemical budgets for a stream, lake, or 

wetland is another way in which solutes can be used to make 

quantitative estimates of surface-water exchange with ground 

water. Conservative chemicals in a watershed are those that 

are not altered by the porous media through which they flow, 

and occur at concentrations for which changes in concentration because of chemical precipitation are not likely to occur.

Conservative chemicals can be used to determine the volume 

of ground water that flows into or out of a surface-water body, 

provided that all other fluxes are known. A common form of 

the chemical-budgeting equation for a lake or wetland is

P(CP) + GWI(CGWI) + SI(CSI) – GWO(CGWO) 

– SO(CSO) = VL(CL) ± R, (3)

where

P is precipitation,

GWI is ground-water flux into lake or wetland,

SI is streamflow into lake or wetland,

E is evaporation,

GWO is flux of lake or wetland water to ground 

water,

SO is streamflow out of lake or wetland,

∆VL is change in lake or wetland volume,

Cx is chemical concentration of hydrologic 

component,

and

R is residual.

Chemical budgets have been calculated in lake and wetland 

studies where water exchange between surface-water bodies and underlying ground water was of interest [see, for 

example, Rawson Lake, Ontario−Schindler and others (1976); 

Thoreau’s Bog, Massachusetts−Hemond (1983); Williams 

Lake, Minnesota−LaBaugh and others (1995); LaBaugh 

and others (1997); multiple lakes in Polk and Highlands 

Counties, Florida−Sacks and others (1998); Lake Kinneret, 

Israel−Rimmer and Gideon (2003)]. The equation can be 

modified to solve for any unknown flow term, provided that 

the remainder of the flow terms are known. The accuracy of 

the method depends greatly on the accuracy of the other flow 

and chemical-concentration measurements. The size of the 

residual term often is considered a general indicator of the 

accuracy of the method, but a small residual does not always 

indicate an accurate chemical balance. LaBaugh (1985) and 

Choi and Harvey (2000) provide examples of the use of error 

analysis to quantify the uncertainty associated with water-flux 

results obtained using this method.

The ratios of the isotopes of oxygen and hydrogen 

present in water have been used for decades to distinguish 

sources of water, including ground-water discharge to surfacewater bodies (for example, Dincer, 1968). These isotopes are 

useful because they are part of the water and not solutes dissolved in the water. The method works well when the degree 

of isotopic fractionation of the water is different for different 

sources of water. The process of evaporation tends to remove 

lighter isotopes, leaving the heavier isotopes behind. Thus, the 

ratio of lighter to heavier isotopes will change over time in the 

water and the water vapor. More detailed explanation of the 

isotopic fractionation in catchment water is given in Kendall 

and others (1995). If the isotopic compositions of different 

sources of water are distinct, then simple mixing models can 

be used to identify sources of water. A brief example is presented here, but more detailed explanations and examples of 

the use of this method can be found in Krabbenhoft and others 

(1994), LaBaugh and others (1997), Sacks (2002) (applied 
Introduction and Characteristics of Flow 25

to lakes), Kendall and others (1995) (a brief description of 

the methods), and Kendall and McDonnell (1998) (detailed 

descriptions of numerous isotopic methods).

For determination of ground-water discharge to streams 

and rivers, a simple two-component mixing model often 

is used:

QSδS = QGWδGW + QPδP (4)

where

Q is discharge,

	 δ	 is the stable-isotopic composition in parts 

per thousand enrichment or depletion 

(“per mil”) relative to a standard,

S is stream water,

GW is ground water,

and 

P is precipitation.

For lakes and wetlands, where sources of water are more 

numerous, slightly more complex mixing models can be used, 

such as those provided by Krabbenhoft and others (1990):

GWI

P E L P E L

GWI L

 
  





( ) D D ( ) D D

D D (5)

or that provided by Krabbenhoft and others (1994):

GWO P V GWI P L L GWI

L

= ⋅ −∆ ⋅ − ⋅ δδ δ

δ , (6)

where

GWI is ground-water flux into lake,

GWO is flux of water from lake to ground water,

P is precipitation,

E is evaporation,

	 ∆VL is change in the volume of the lake,

and

δX is per mil value for hydrologic component.

Where equations 5 and 6 are derived from equation 3 applied 

to stable isotopes at steady state:

d(VδL)/dt = GWI δGWI + P δP + Si δSi

– GWO δL –E δE– So δL = 0. (7)

Investigation of ground-water discharge into inland and 

marine surface water also is feasible through measurement 

of radon and radium isotopes (Corbett and others, 1998; 

Moore, 2000). In the radon isotope method, a mass balance is 

constructed for radon-222 (222Rn), which is a chemically and 

biologically inert radioactive gas formed by the disintegration 

of the parent nuclide radium (Corbett and others, 1998, 1999). 

Because radon is a gas, radon in water in contact with the 

atmosphere will be lost from that water because of volatilization. Thus, ground water commonly contains higher activities 

of 222Rn than does surface water, from 3 to 4 orders of magnitude greater (Burnett and others, 2001). 222Rn is a radioactive 

daughter isotope of radium 226 (226Ra) and has a half life of 

3.82 days. Determination of the activity of 222Rn and 226Ra in 

surface water enables the calculation of the 222Rn excess—how 

much more 222Rn is present in surface water than would be 

expected based on the 226Ra content of the water. Determination of the activity of 222Rn and 226Ra in sediment water or 

ground water is used to determine the 222Rn flux into surface 

water (Cable and others, 1996; Corbett and others, 1998), 

which can account for the excess 222Rn in the surface water. 

The mass balance or flux of 222Rn has been used to determine 

ground-water discharge to several types of surface-water bodies (Kraemer and Genereaux, 1998): in streams, such as the 

Bickford watershed, Massachusetts (Genereaux and Hemond, 

1990); rivers, such as the Rio Grande de Manati, Puerto Rico 

(Ellins and others, 1990); lakes, such as Lake Kinneret, Israel 

(Kolodny and others, 1999); estuaries, such as Chesapeake 

Bay (Hussain and others, 1999), Charlotte Harbor, Florida 

(Miller and others, 1990), and Florida Bay (Corbett and others, 

1999), as well as the coastal ocean, such as in Kanaha Bay, 

Oahu, Hawaii (Garrison and others, 2003); the Gulf of Mexico 

off of Florida (Cable and others, 1996; Burnett and others, 

2001); and the Atlantic Ocean off the coast of South Carolina 

(Corbett and others, 1998).

In the radium isotope method, the surface-water activities of the four naturally occurring radium isotopes—226Ra, 228Ra, 223Ra, and 224Ra—are compared to activities in sediment 

water or ground water to determine fluxes (Moore, 2000). 

The source of the radium isotopes is the decay of uranium 

and thorium in sediments or rocks. Water in contact with solid 

materials containing the source of the isotopes will accumulate the isotopes. Ground water will accumulate more of the 

isotopes because of water’s presence within the matrix of the 

sediments or rocks. Surface waters will accumulate less of 

the isotopes because the sediments or rocks are less abundant 

relative to the water (Kraemer, 2005). Kraemer indicates the 

ratio of the longer lived isotopes (226Ra half-life of 1,601 years, 228Ra half-life of 5.8 years) can be used as an indicator of 

the types of sediments or rocks through which ground water 

has traveled, because of differences in uranium and thorium 

content between rock types. Kraemer (2005) also notes that 

the short-lived isotopes (223Ra half life of 11.4 days, and 224Ra 

half-life of 3.7 days) provide some indication of the timing of 

ground-water discharge. Naturally occurring radium isotopes 

have been useful in the identification of ground-water inflow 

to lakes, such as Cayuga Lake, New York (Kraemer, 2005), 

freshwater wetlands in the Florida Everglades (Krest and 

Harvey, 2003), estuarine wetlands, North Inlet salt marsh, 

South Carolina (Krest and others, 2000), and coastal waters 

in the central South Atlantic Bight (Moore, 2000).
26 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Thermal Profiling

Measurements of temperature have been used to 

determine qualitatively the locations of rapid discharge of 

ground water to surface water; common measurement methods 

include towing a tethered temperature probe, in-situ measurements of temperature, and thermal imagery (Lee, 1985; 

Baskin, 1998; Rosenberry and others, 2000). Temperature also 

can be measured at different depths beneath a stream or lake to 

determine the rate of vertical flow through a surface-water bed 

either into or out of the surface-water body (Lapham, 1989). 

This method is effective when flow through the lakebed is 

sufficient to allow advective processes to be significant relative 

to conductive temperature signals. The method requires 

multiple measurements of temperature over weeks or months 

and the simultaneous solution of the flow of fluid and heat in 

one dimension. Depths of temperature measurement typically 

extend up to 3 to 6 meters beneath the sediment bed. The 

solution requires the assumption that flow is vertical through 

the surface-water bed and that the media are homogeneous and 

isotropic. Taniguchi (1993) used seasonal changes in sediment 

temperature beneath a surface-water body to develop type 

curves that can be used to estimate vertical fluxes through the 

surface-water bed.

Subsediment temperature has been used over short 

distances beneath the surface-water bed and makes use of 

the temperature response in the sediments to diurnal changes 

in surface-water temperature (Constantz and others, 1994; 

Stonestrom and Constantz, 2003). This method adjusts 

parameters in a one-dimensional, variably saturated heattransport model (VS2DH) [developed in the USGS (Healy 

and Ronan, 1996)] until the simulation results match the 

temperature data collected beneath the surface-water body. 

Sediment temperature measurements and data also have 

been used to determine streamflow frequency in ephemeral 

stream channels (Constantz and others, 2001; Stonestrom 

and Constantz, 2003). This method is described in greater 

detail in Chapter 4. Conant (2004) used measurements of 

hydraulic-head gradient and hydraulic conductivity in wells 

installed in a streambed to determine rates of exchange 

between ground water and surface water. Conant then developed an empirical relation between streambed flux and 

streambed temperature relative to stream-water temperature 

and used the empirical relation to indicate rate of discharge of 

ground water to the stream at locations where only streambed 

temperature was measured.

Use of Specific-Conductance Probes

Specific-conductance probes are another tool that can 

be useful for locating areas of ground-water discharge to 

surface waters (Lee, 1985; Vanek and Lee, 1991; Harvey 

and others, 1997) (fig. 19). Such probes are suspended from 

a boat with a cable connecting the probes to a specificconductance meter on board the boat. The housing for 

the electrically conductive probes is designed to maintain 

contact with the sediments (Lee, 1985) so that the probes 

are dragged through bottom sediments at a depth of 1 to 

3 centimeters (Vanek and Lee, 1991). This method depends 

on having the existence of a difference in the electrical conductance of surface and ground water great enough to be 

detected by the sensors (probes) and thus to identify points or 

areas of ground-water discharge to the surface water. Thus, 

saline waters receiving ground-water discharge of less salinity (Vanek and Lee, 1991) or fresh surface waters receiving 

more mineralized ground-water discharge (Harvey and others, 1997) are environments where this technique is effective. Changes in electrical conductance, however, also may 

reflect changes in sediment type so that the technique should 

be considered only as a reconnaissance tool. The identification of places where ground-water discharge may be occurring should be verified by other, complementary techniques 

(Vanek and Lee, 1991). Specific-conductance and temperature 

probes have been used in this way along many kilometers of 

river reaches in combination with Global Positioning System 

information to determine the precise locations of groundwater discharge and their variation with season (Vaccaro 

and Maloy, 2006). Conductance

Distance

Figure 19. Example of the use of a towed specific-conductance 

probe to identify ground-water discharge to surface waters 

(from Harvey and others, 1997, used in accordance with usage 

permissions of the American Geophysical Union). The sediment 

probe is being towed behind a small boat. The probe is used to 

detect areas of more electrically conductive ground-water inflow. 

In saline waters, the probe is used to detect less electrically 

conductive fresh ground-water inflow.
Introduction and Characteristics of Flow 27

Electrical Resistivity Profiling

Electrical geophysical survey methods are applicable 

to delineating submarine ground-water discharge (Loke and 

Lane, 2004). Salinity differences in water can be detected by 

the resistance to the passage of current between electrodes. 

Fresh or weakly saline waters will be more resistant to movement of an electric current than more saline waters. Two 

resistivity data acquisition geometries commonly are used: 

(1) continuous resistivity profiling (Belaval and others, 2003; 

Manheim and others, 2004; Day-Lewis and others, 2006), and 

(2) marine resistivity (Taniguchi and others, 2006). In continuous resistivity profiling, a streamer comprising a set of floating 

electrodes spaced at a regular interval is towed on the water 

surface behind a boat. As the boat travels along a transect, 

electrical current is applied at a fixed time interval at one or 

more electrode pairs, and electrical potentials are measured 

simultaneously between other electrode pairs. At the same 

time, water depths along the transect are measured with echo 

sounding. In marine resistivity profiling, measurements are 

made using electrodes placed on the water bottom. Regardless 

of the acquisition geometry, data are inverted to produce 

two-dimensional cross sections, or tomograms, of subsurface 

resistivity. Such data can indicate locations within a transect 

where submarine ground-water discharge is occurring, as well 

as delineating the subsurface saltwater/freshwater interface or 

geologic structure. Tomograms are commonly interpreted in 

the context of direct, discrete measurements of conductivity, 

temperature, and depth.

Hydraulic Potentiomanometer

(Portable Wells) Measurements

Many devices have been designed to be installed 

through the bed of a surface-water body to measure the vertical hydraulic-head gradient beneath the surface-water body. 

These devices provide a direct measurement of hydraulic head 

relative to surface-water stage at the depth to which the probe 

is inserted beneath the surface-water bed. One of the most 

commonly used devices of this type is the hydraulic potentiomanometer (fig. 20), also sometimes called a minipiezometer 

Figure 20. A, Hydraulic potentiomanometer with users 

demonstrating hydraulic-head difference between surface water 

and ground water. The hydraulic head of the river (right side 

of the board) is higher than the hydraulic head of the ground 

water (left side of the board), indicating a downward gradient 

(from Simonds and Sinclair, 2002). Photograph by Kirk A. Sinclair, 

Washington State Department of Ecology, 2002. B, Components of 

a hydraulic-potentiomanometer system (from Winter and others, 

1988, copyright 1988 by the American Society of Limnology and 

Oceanography, Inc., used with permission).

Probe

Manometer

board

Tube A

Tube C Valve

Valve or 

clamp

Pump

To optional

sample bottle

Water 

surface

Tube B

Filter

Lake bed

A B
28 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

(Winter and others, 1988). Although this device does not provide direct measurements of flow across the sediment-water 

interface, it is useful for making qualitative determinations of 

direction of flow across the sediment-water interface. Estimates of hydraulic conductivity also can be made on the basis 

of the amount of suction required to pull water through the 

screen at the end of the probe. These devices often are used 

in conjunction with a network of wells to obtain additional 

hydraulic-head data along shoreline segments where wells are 

not or cannot be situated. Details about use of these devices is 

provided in Chapter 2.

Seepage Meter Measurements

Seepage meters are devices that isolate a small area of 

the bed of a surface-water body and measure the flow of water 

across that area. References as early as 1944 indicate that early 

seepage meters were designed to measure water loss through 

unlined canals (Carr and Winter, 1980). Beginning in the early 

1970s, seepage meters have been used in lakes, rivers, wetlands, and estuaries to measure flows between surface water 

and ground water in natural settings. Use in coastal environments has increased during recent years (Cable and others, 

1997). One of the most common devices, called a half-barrel 

seepage meter, uses a cut-off end of a steel (or plastic) storage 

drum to isolate a small circular area of the surface-water bed, 

and a plastic bag is attached to the barrel to register the change 

in water volume over the time of bag attachment (Lee, 1977; 

Lee and Cherry, 1978) (fig. 21). More details about the use 

and interpretation of data from seepage meters are included in 

Chapter 2. Many device modifications have been made to the 

basic design of seepage meters for use in deep water, soft sediments, shallow water, and areas exposed to large waves.

Many investigations of surface-water and ground-water 

interaction require integrating point measurements of water 

flux in order to interpret the total flow between surface water 

and ground water. The most common method is to average 

point measurements and apply that average value to all or 

part of the surface-water body of interest. This method is not 

appropriate, however, where ground-water flux into a surface 

water declines with greater distance from shore. If data are 

collected along transects perpendicular to the shore, a curve 

can be fit through the data. Because ground-water flow to 

surface water commonly is distributed exponentially with 

distance from shore, exponential curves have been fit through 

transect data, and the equation for the curve has been used 

to calculate water flux for an area deemed to be representative of the transect point measurements (for example, Fellows 

and Brezonik, 1980). Where ground-water flux is not exponentially distributed with distance from shore, a plot of point 

measurements of seepage flux with distance from shore is 

made, and the area under the curve can be determined to represent total seepage for a unit width of shoreline. That value can 

then be multiplied by an appropriate shoreline length to determine a flux volume for a specific area of the surface-water 

body. If point measurements are made at a sufficient number 

of transects, ground-water flux for an area of a surface-water 

body can be determined.

Biological Indicators

The biological response to conditions of flow at the 

sediment-water interface can be an indicator of the direction and relative magnitude of flow. The growing field of 

ground-water ecology has made frequent use of distributions 

of specific types of plants and animals as an indicator of 

ground-water/surface-water interaction (Danielopol, 1984; 

Danielopol and others, 1997; Lodge and others, 1989; Malard 

and others, 1996; Goslee and others, 1997; Wetzel, 1999) 

(fig. 22). These methods are useful reconnaissance tools to aid 

in locating areas in need of more detailed investigations. Typically, these methods involve identifying species or groups of 

species of plants or animals that are known to thrive in places 

where ground water discharges to surface water, but some of 

the indicators also indicate areas where surface water flows 

into ground water. Identification of specific plant and animal 

species is necessary for use of these methods, but some of the 

species are readily identifiable without requiring intensive biological or ecological training (Rosenberry and others, 2000).

Water surface

Seepage cylinder

Bag

Water

Sediment

Bag

Water

Sediment

Water surface

Figure 21. Full-section view of seepage meter showing details 

of placement in the sediment (modified from Lee and Cherry, 1978, 

used with permission of the Journal of Geoscience Education).
Introduction and Characteristics of Flow 29

Figure 22. Marsh marigold in Shingobee Lake, Minnesota. Presence indicates location of ground-water discharge to the 

lake. (Photographs by Donald O. Rosenberry, U.S. Geological Survey.)
30 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

References

Adamowski, K., and Feluch, W., 1991, Application of 

nonparametric regression to groundwater level prediction: Canadian Journal of Civil Engineering, v. 18, no. 4, 

p. 600–606.

Aley, T.J., and Fletcher, M.W., 1976, The water tracer’s 

cookbook—A guide to the art and science of water tracing 

materials with particular emphasis on the use of fluorescent 

dyes, Lycopodium spores, and bacteriophage in groundwater investigations: Missouri Speleology, v. 16, no. 3, 32 p.

Alley, W.M., Reilly, T.E., and Franke, O.L., 1999, Sustainability of ground-water resources: U.S. Geological Survey 

Circular 1186, 79 p.

Andrews, C.B., and Anderson, M.P., 1978, Impact of a power 

plant on the ground-water system of a wetland: Ground 

Water, v. 16, no. 2, p. 105–111.

Asbury, C.E., 1990, The role of groundwater seepage in sediment chemistry and nutrient budgets in Mirror Lake, New 

Hampshire: Ithaca, Cornell University, Ph.D. dissertation, 

275 p.

Attanayake, M.P., and Waller, D.H., 1988, Use of seepage 

meters in a groundwater-lake interaction study in a fractured 

rock basin—A case study: Canadian Journal of Civil Engineering, v. 15, p. 984–989.

Bacchus, S.T., 2001, Knowledge of groundwater responses—A 

critical factor in saving Florida’s threatened and endangered 

species, Part 1—Marine ecological disturbances: Endangered 

Species UPDATE, v. 18, no. 3, p. 79–90.

Bacchus, S.T., 2002, The “ostrich” component of the multiple 

stressor model—Undermining South Florida, in Porter, 

J.W., and Porter, K.G., eds., The Everglades, Florida Bay, 

and Coral Reefs of the Florida Keys—An Ecosystem 

Sourcebook: Boca Raton, CRC Press, p. 677–748.

Banks, W.S.L., Paylor, R.L., and Hughes, W.B., 1996, Using 

thermal-infrared imagery to delineate ground-water discharge: Ground Water, v. 34, no. 3, p. 434–443.

Barlow, P.M., and Dickerman, D.C., 2001, Numerical 

simulation and conjunctive-management models of the 

Hunt-Annaquatucket-Pettaquamscutt stream-aquifer system, Rhode Island: U.S. Geological Survey Professional 

Paper 1636, 88 p., one map sheet.

Barlow, P.M., and Wild, E.C., 2002, Bibliography on the 

occurrence and intrusion of saltwater in aquifers along the 

Atlantic Coast of the United States: U.S. Geological Survey 

Open-File Report 2002–235, 30 p.

Baskin, R.L., 1998, Locating shoreline submarine springs in 

two Utah lakes using thermal imagery, in Pitman, J.K., and 

Carroll, A.R., eds., Modern & ancient lake systems—New 

problems and perspectives: Salt Lake City, Utah Geological 

Association, v. 26, p. 51–57.

Belanger, T.V., and Kirkner, R.A., 1994, Groundwater/surface 

water interaction in a Florida augmentation lake: Lake and 

Reservoir Management, v. 8, no. 2, p. 165–174.

Belaval, Marcel, Lane, J.W., Jr., Lesmes, D.P., and Kineke, 

G.C., 2003, Continuous-resistivity profiling for coastal 

groundwater investigations—Three case studies, in Symposium on the Application of Geophysics to Engineering 

and Environmental Problems (SAGEEP), April 6–10, 2003, 

San Antonio, Texas, Proceedings: Denver, Colorado, Environmental and Engineering Society, CD–ROM, 14 p.

Bencala, K.E., McKnight, D.M., and Zellweger, G.W., 1990, 

Characterization of transport in an acidic and metal-rich 

mountain stream based on a lithium tracer injection and 

simulations of transient storage: Water Resources Research, 

v. 26, no. 5, p. 989–1000.

Beven, K.J., ed., 1997, Distributed hydrological modelling—

Application of the TOPMODEL concept: Chichester, Wiley, 

348 p.

Beven, K.J., and Feyen, J., 2002, The future of distributed 

modeling: Hydrological Processes, v. 1, p. 169–172.

Beven, K.J., Kirkby, M.J., Schofield, N., and Tagg, A.F., 

1984, Testing a physically based flood-forecasting model 

(TOPMODEL) for three U.K. catchments: Journal of 

Hydrology, v. 69, p. 119–143.

Bokuniewicz, Henry, 1980, Groundwater seepage into Great 

South Bay, New York: Estuarine and Coastal Marine Science, 

v. 10, p. 437–444.

Bouwer, H., and Maddock, T., III, 1997, Making sense of the 

interactions between groundwater and streamflow—Lessons 

for water masters and adjudicators: Rivers, v. 6, no. 1, 

p. 19–31.

Buchtele, J., Buchtelová, M., Gallart, F., Latron, J., Llorens, 

P., Salvany, C., and Herrmann, A., 1998, Rainfall-runoff 

processes modelling using SACRAMENTO and BROOK 

models in the Cal Rodó catchment (Pyrenees, Spain), 

Conference on Catchment Hydrological and Biochemical 

Processes in Changing Environment: Liblice, Czechoslovakia, p. 13–16.

Burnett, W.C., Kim, G., and Lane-Smith, D., 2001, A continuous monitor for assessment of 222Rn in the coastal ocean: 

Journal of Radioanalytical and Nuclear Chemistry, v. 249, 

no. 1, p. 167–172.
Introduction and Characteristics of Flow 31

Cable, J.E., Bugna, G.C., Burnett, W.C., and Chanton, J.P., 

1996, Application of 222Rn and CH4 for assessment of 

groundwater discharge to the coastal ocean: Limnology and 

Oceanography, v. 41, no. 6, p. 1347–1353.

Cable, J.E., Burnett, W.C., Chanton, J.P., Corbett, D.R., and 

Cable, P.H., 1997, Field evaluation of seepage meters in the 

coastal marine environment: Estuarine, Coastal and Shelf 

Science, v. 45, no. 3, p. 367–375.

Cambareri, T.C., and Eichner, E.M., 1998, Watershed delineation and ground-water discharge to a coastal embayment: 

Ground Water, v. 36, no. 4, p. 626–634.

Campbell, C.W., and Keith, A.G., 2001, Karst ground-water 

hydrologic analyses based on aerial thermography: Hydrological Science and Technology, Special Issue, v. 17, 

no. 1–4, p. 59–68.

Carr, M.R., and Winter, T.C., 1980, An annotated bibliography 

of devices developed for direct measurement of seepage: 

U.S. Geological Survey Open-File Report 80–344, 38 p.

Carter, J.M., Driscoll, D.G., Williamson, J.E., and Lindquist, 

V.A., 2002, Atlas of water resources in the Black Hills area, 

South Dakota: U.S. Geological Survey Hydrologic Investigations Atlas HA–747, 120 p.

Cheng, Xiangxue, and Anderson, M.P., 1993, Numerical 

simulation of ground-water interaction with lakes allowing for fluctuating lake levels: Ground Water, v. 31, no. 6, 

p. 929–933.

Childress, C.J.O., Sheets, R.A., and Bair, E.S., 1991, Hydrology and water quality near the South Well Field, southern 

Franklin County, Ohio, with emphasis on the simulation of ground-water flow and transport of Scioto River: 

U.S. Geological Survey Water-Resources Investigations 

Report 91–4080, 78 p.

Choi, Jungyill, and Harvey, J.W., 2000, Quantifying timevarying ground-water discharge and recharge in wetlands 

of the northern Florida Everglades: Wetlands, v. 20, no. 3, 

p. 500–511.

Committee on Hydrologic Science, National Reseach Council, 

2004, Groundwater fluxes across interfaces: Washington, 

D.C., The National Academies Press, 85 p.

Conant, Brewster, Jr., 2004, Delineating and quantifying 

ground-water discharge zones using streambed temperatures: Ground Water, v. 42, no. 2, p. 243–257.

Constantz, James, Stonestrom, David, Stewart, A.E., 

Niswonger, Rich, and Smith, T.R., 2001, Analysis of 

streambed temperatures in ephemeral channels to determine streamflow frequency and duration: Water Resources 

Research, v. 37, no. 2, p. 317–328.

Constantz, James, Thomas, C.L., and Zellweger, G., 1994, 

Influence of diurnal variations in stream temperature on 

streamflow loss and groundwater recharge: Water Resources 

Research, v. 30, no. 12, p. 3253–3264.

Corbett, D.R., Burnett, W.C., Cable, P.H., and Clark, S.B., 

1998, A multiple approach to the determination of radon 

fluxes from sediments: Journal of Radioanalytical and 

Nuclear Chemistry, v. 236, p. 247–252.

Corbett, D.R., Chanton, Jeffrey, Burnett, William, Dillon, 

Kevin, Rutkowski, Christine, and Fourqurean, J.W., 1999, 

Patterns of groundwater discharge into Florida Bay: Limnology and Oceanography, v. 44, no. 4, p. 1045–1055.

Danielopol, D.L., 1984, Ecological investigations on the 

alluvial sediments of the Danube in the Vienna area—A 

phreatobiological project: Verhandlungen Internationale 

Vereiningen Limnologie, v. 22, p. 1755–1761.

Danielopol, D.L., Rouch, R., Pospisil, P., Torreiter, P., and 

Moeszlacher, F., 1997, Ecotonal animal assemblages; their 

interest for groundwater studies, in Gibert, J., Mathieu, 

J., and Fournier, F., eds., Groundwater/surface water 

ecotones—Biological and hydrological interactions and 

management options: Cambridge, Cambridge University 

Press, p. 11–20.

Danskin, W.R., 1998, Evaluation of the hydrologic system 

and selected water-management alternatives in the Owens 

Valley, California: U.S. Geological Survey Water-Supply 

Paper 2370–H, 175 p., 6 pls. in pocket.

Day-Lewis, F.D., White, E.A., Belaval, M., Johnson, C.D., 

and Lane, J.W., Jr., 2006, Continuous resistivity profling to 

delineate submarine ground-water discharge—Examples 

and limitations: The Leading Edge, v. 25, no. 6, p.724–728.

Dincer, T., 1968, The use of oxygen 18 and deuterium concentrations in the water balance of lakes: Water Resources 

Research, v. 4, no. 6, p. 1289–1306.

Dokulil, M.T., Teubner, K., and Donabaum, K., 2000, Restoration of a shallow, ground-water fed urban lake using a 

combination of internal management strategies—A case 

study: Advances in Limnology, v. 55, p. 271–282.

Donato, M.M., 1998, Surface-water/ground-water relations in 

the Lemhi River Basin, East-Central Idaho: U.S. Geological Survey Water-Resources Investigations Report 98–4185, 

29 p.

Doss, P.K., 1993, Nature of a dynamic water table in a system 

of non-tidal freshwater coastal wetlands: Journal of Hydrology, v. 141, p. 107–126.

Dumouchelle, D.H., 2001, Evaluation of ground-water/

surface-water relations, Chapman Creek, west-central, Ohio, 

by means of multiple methods: U.S. Geological Survey 

Water-Resources Investigations Report 2001–4202, 13 p.
32 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Ellins, K.K., Roman-Mas, A., and Lee, R., 1990, Using 222Rn 

to examine groundwater/surface discharge interaction in the 

Rio Grande de Manati, Puerto Rico: Journal of Hydrology, 

v. 115, p. 319–341.

Erickson, D.R., 1981, A study of littoral groundwater seepage at Williams Lake, Minnesota, using seepage meters and 

wells: Minneapolis, University of Minnesota, M.S. thesis, 

135 p.

Federer, C.A., and Lash, D., 1978, BROOK—A hydrologic 

simulation model for eastern forests: Water Resources 

Research Center, University of New Hampshire Research 

Report no. 19, 84 p.

Fellows, C.R., and Brezonik, P.L., 1980, Seepage flow into 

Florida lakes: Water Resources Bulletin, v. 16, no. 4, 

p. 635–641.

Fenske, J.P., Leake, S.A., and Prudic, D.E., 1996, Documentation of a computer program (RES1) to simulate leakage 

from reservoirs using the modular finite-difference groundwater flow model (MODFLOW): U.S. Geological Survey 

Open-File Report 96–364, 51 p.

Fischer, W.A., Davis, D.A., and Sousa, T.M., 1966, Fresh-water 

springs of Hawaii from infrared images: U.S. Geological 

Survey Hydrologic Atlas 218, 1 map.

Fraser, C.J.D., Roulet, N.T., and Lafleur, M., 2001, Groundwater flow pattern in a large peatland: Journal of Hydrology, 

v. 246, p. 142–154.

Galloway, D.L., Alley, W.M., Barlow, P.M., Reilly, T.E., and 

Tucci, P., 2003, Evolving issues and practices in managing 

ground-water resources—Case studies on the role of science: U.S. Geological Survey Circular 1247, 73 p.

Garrett, J.W., Bennett, D.H., Frost, F.O., and Thurow, R.F., 

1998, Enhanced incubation success for Kokanee spawning 

in groundwater upwelling sites in a small Idaho stream: 

North American Journal of Fisheries Management, v. 18, 

no. 4, p. 925–930.

Garrison, G.H., Glenn, C.R., and McMurtry, G.M., 2003, 

Measurement of submarine groundwater discharge in Kahana 

Bay, O’ahu, Hawai’i: Limnology and Oceanography, v. 48, 

no. 2, p. 920–928.

Genereux, D.P., and Hemond, H.F., 1990, Naturally occurring 

radon 222 as a tracer for streamflow generation—Steadystate methodology and field application: Water Resources 

Research, v. 26, no. 12, p. 3065–3075.

Glennon, Robert, 2002, Water follies—Groundwater pumping 

and the fate of America’s fresh waters: Washington, D.C., 

Island Press, 314 p.

Goslee, S.C., Brooks, R.P., and Cole, C.A., 1997, Plants as 

indicators of wetland water source: Plant Ecology, v. 131, 

p. 199–206.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. Geological Survey Open-File Report 2000–92, 121 p.

Harte, P.T., Flynn, R.J., Kiah, R.G., Severance, T., and Coakley, 

M.F., 1997, Information on hydrologic and physical properties of water to assess transient hydrology of the MilfordSouhegan glacial-drift aquifer, Milford, New Hampshire: 

U.S. Geological Survey Open-File Report 97–414, 45 p.

Harvey, F.E., Lee, D.R., Rudolph, D.L., and Frape, S.K., 1997, 

Locating groundwater discharge in large lakes using bottom 

sediment electrical conductivity mapping: Water Resources 

Research, v. 33, no. 11, p. 2609–2615.

Harvey, J.W., and Wagner, B.J., 2000, Quantifying hydrologic 

interactions between streams and their subsurface hyporheic 

zones, in Jones, J.B., and Mulholland, P.J., eds., Streams 

and ground waters: San Diego, Academic Press, p. 3–44.

Healy, R.W., and Ronan, A.D., 1996, Documentation of 

computer program VS2DH for simulation of energy transport in variably saturated porous media—Modification of 

the U.S. Geological Survey's computer program VS2DT: 

U.S. Geological Survey Water-Resources Investigations 

Report 96–4230, 36 p.

Hemond, H.F., 1983, The nitrogen budget of Thoreau’s Bog: 

Ecology, v. 64, p. 94–109.

Herbert, L.R., and Thomas, B.K., 1992, Seepage study of 

the Bear River including Cutler Reservoir in Cache Valley, 

Utah and Idaho: Salt Lake City, Utah Department of Natural 

Resources, Division of Water Rights, State of Utah Department of Natural Resources Technical Publication no. 105, 

18 p.

Hill, M.C., Lennon, G.P., Brown, G.A., Hebson, C.S., and 

Rheaume, S.J., 1992, Geohydrology of simulation of 

ground-water flow in the valley-fill deposits in the Ramapo 

River Valley, New Jersey: U.S. Geological Survey WaterResources Investigations Report 90–4151, 92 p.

Hussain, N., Church, T.M., and Kim, G., 1999, Use of 222Rn 

and 226Ra to trace groundwater discharge into the Chesapeake Bay: Marine Chemistry, v. 65, p. 127–134.

Hutson, S.S., Barber, N.L., Kenny, J.F., Linsey, K.S., Lumia, 

D.S., and Maupin, M.A., 2004, Estimated use of water in 

the United States in 2000: U.S. Geological Survey Circular 1268, 52 p.
Introduction and Characteristics of Flow 33

Jacobs, K.L., and Holway, J.M., 2004, Managing for sustainability in an arid climate—Lessons learned from 20 years of 

groundwater management in Arizona, USA: Hydrogeology 

Journal, v. 12, no. 1, p. 52–65.

Jaquet, N.G., 1976, Ground-water and surface-water relationships in the glacial province of northern Wisconsin—Snake 

Lake: Ground Water, v. 14, no. 2, p. 194–199.

Jobson, H.E., and Harbaugh, A.W., 1999, Modifications to the 

diffusion analogy surface-water flow model (DAFLOW) for 

coupling to the modular finite-difference ground-water flow 

model (MODFLOW): U.S. Geological Survey Open-File 

Report 99–217, 107 p.

Jones, W.K., ed., 1984, Water tracing special issue: National 

Speleological Society Bulletin, v. 46, no. 2, 48 p.

Johannes, R.E., 1980, The ecological significance of the 

submarine discharge of groundwater: Marine Ecology—

Progress Series, v. 3, p. 365–373.

Johannes, R.E., and Hearn, C.J., 1985, The effect of submarine 

groundwater discharge on nutrient and salinity regimes in 

a coastal lagoon off Perth, Western Australia: Estuarine, 

Coastal and Shelf Science, v. 21, p. 789–800.

Kaleris, V., 1998, Quantifying the exchange rate between 

groundwater and small streams: Journal of Hydraulic 

Research, v. 36, no. 6, p. 913–932.

Kilpatrick, F.A., and Cobb, E.D., 1985, Measurement of discharge using tracers: U.S. Geological Survey, Techniques of 

Water-Resources Investigations, book 3, chap. A–16, 73 p.

Kendall, Carol, and McDonnell, J.J., eds., 1998, Isotope tracers in catchment hydrology: New York, Elsevier Science 

Publishers, 839 p.

Kendall, Carol, Sklash, M.G., and Bullen, T.K., 1995, Isotope tracers of water and solute sources in catchments, in

Trudgill, S.T., ed., Solute modelling in catchment systems: 

New York, John Wiley & Sons, Ltd., p. 261–303.

Kimball, Briant, 1997, Use of tracer injections and synoptic 

sampling to measure metal loading from acid mine drainage: U.S. Geological Survey Fact Sheet 245–96, 4 p.

Konrad, C.P., Drost, B.W., and Wagner, B.J., 2003, Hydrogeology of the unconsolidated sediments, water quality, and 

ground-water/surface-water exchanges in the Methow River 

Basin, Okanogan County, Washington: U.S. Geological 

Survey Water-Resources Investigations Report 2003–4244, 

137 p.

Kolodny, Yehoshua, Katz, Amitai, Starinsky, Abraham, Moise, 

Tamar, and Simon, Ehud, 1999, Chemical tracing of salinity 

sources in Lake Kinneret (Sea of Galilee), Israel: Limnology and Oceanography, v. 44, no. 4, p. 1035–1044.

Krabbenhoft, D.P., and Anderson, M.P., 1986, Use of a 

numerical ground-water flow model for hypothesis testing: 

Ground Water, v. 24, p. 49–55.

Krabbenhoft, D.P., Anderson, M.P., and Bowser, C.J., 1990, 

Estimating groundwater exchange with lakes, 2—Calibration 

of a three-dimensional, solute transport model to a stable 

isotope plume: Water Resources Research, v. 26, no. 10, 

p. 2455–2462.

Krabbenhoft, D.P., Bowser, C.J., Kendall, C., and Gat, J.R., 

1994, Use of oxygen-18 and deuterium to assess the hydrology of groundwater-lake systems, in Baker, L.A., ed., Environmental Chemistry of Lakes and Reservoirs: American 

Chemical Society, Advances in Chemistry Series no. 237, 

p. 67–90.

Kraemer, T.F., 2005, Radium isotopes in Cayuga Lake, New 

York—Indicators of inflow and mixing processes: Limnology and Oceanography, v. 50, no. 1, p. 158–168.

Kraemer, T.F., and Genereux, D.P., 1998, Applications of 

uranium and thorium series radionuclides in catchment 

hydrology studies, in Kendall, Carol, and McDonnell, J.J., 

eds., Isotope tracers in catchment hydrology: Amsterdam, 

Elsevier, p. 679–722.

Krest, J.M., and Harvey, J.W., 2003, Using natural distributions of short-lived radium isotopes to quantify ground 

water discharge and recharge: Limnology and Oceanography, v. 48, no. 1, p. 290–298.

Krest, J.M., Moore, W.S., Gardner, L.R., and Morris, J.T., 

2000, Marsh nutrient export supplied by groundwater 

discharge—Evidence from radium measurements: Global 

Biogeochemical Cycles, v. 14, no. 1, p. 167–176.

LaBaugh, J.W., 1985, Uncertainty in phosphorus retention, 

Williams Fork Reservoir, Colorado: Water Resources 

Research, v. 21, no. 11, p. 1684–1692.

LaBaugh, J.W., Rosenberry, D.O., and Winter, T.C., 1995, 

Groundwater contribution to the water and chemical budgets of Williams Lake, Minnesota, 1980–1991: Canadian 

Journal of Fisheries and Aquatic Science, v. 52, p. 754–767.

LaBaugh, J.W., Winter, T.C., Rosenberry, D.O., Schuster, P.F., 

Reddy, M.M., and Aiken, G.A., 1997, Hydrological and 

chemical estimates of the water balance of a closed-basin 

lake in north-central Minnesota: Water Resources Research, 

v. 33, no. 12, p. 2799–2812.

Lapham, W.W., 1989, Use of temperature profiles beneath 

streams to determine rates of vertical ground-water flow 

and vertical hydraulic conductivity: U.S. Geological Survey 

Water-Supply Paper 2337, 35 p.
34 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Leavesley, G.H., and Hay, L., 1998, The use of coupled 

atmospheric and hydrological models for water-resources 

management in headwater basins, in Kovar, K., Tappeiner, 

U., Peters, N.E., and Craig, R.G., eds., Hydrology, water 

resources, and ecology in headwaters, Meran, Italy: Meran, 

Italy IAHS-AISH Publication, p. 259–265.

Leavesley, G.H., Lichty, R.W., Troutman, B.M., and Saindon, 

L.G., 1983, Precipitation-runoff modeling system—User's 

manual: U.S. Geological Survey Water-Resources Investigations Report 83–4238, 207 p.

Leavesley, G.H., Markstrom, S.L., Restrepo, P.J., and Viger, 

R.J., 2002, A modular approach to addressing model 

design, scale, and parameter estimation issues in distributed hydrological modeling: Hydrological Processes, v. 16, 

p. 173–187.

Leavesley, G.H., Restrepo, P.J., Markstrom, S.L., Dixon, M., 

and Stannard, L.G., 1996, The modular modeling system—

MMS, User's manual: U.S. Geological Survey Open-File 

Report 96–151, 142 p.

Lee, D.R., 1977, A device for measuring seepage flux in lakes 

and estuaries: Limnology and Oceanography, v. 22, no. 1, 

p. 140–147.

Lee, D.R., 1985, Method for locating sediment anomalies in 

lakebeds that can be caused by groundwater flow: Journal of 

Hydrology, v. 79, p. 187–193.

Lee, D.R., and Cherry, J.A., 1978, A field exercise on groundwater flow using seepage meters and minipiezometers: Journal of Geological Education, v. 27, p. 6–20.

Lee, D.R., Cherry, J.A., and Pickens, J.F., 1980, Groundwater 

transport of a salt tracer through a sandy lakebed: Limnology and Oceanography, v. 25, no. 1, p. 45–61.

Lee, T.M., and Swancar, Amy, 1997, Influence of evaporation, ground water, and uncertainty in the hydrologic budget 

of Lake Lucerne, a seepage lake in Polk County, Florida: 

U.S. Geological Survey Water-Supply Paper 2439, 61 p.

Linderfelt, W.R., and Turner, J.V., 2001, Interaction between 

shallow groundwater, saline surface water and nutrient discharge in a seasonal estuary—The Swan–Canning system: 

Hydrological Processes, v. 15, p. 2631–2653.

Lindgren, R.J., and Landon, M.K., 1999, Effects of groundwater withdrawals on the Rock River and associated valley 

aquifer, eastern Rock County, Minnesota: U.S. Geological 

Survey Water-Resources Investigations Report 99–4157, 

103 p.

Lodge, D.M., Krabbenhoft, D.P., and Striegl, R.G., 1989, A 

positive relationship between groundwater velocity and submersed macrophyte biomass in Sparkling Lake, Wisconsin: 

Limnology and Oceanography, v. 34, no. 1, p. 235–239.

Loke, M.H., and Lane, J.W., Jr., 2004, Inversion of data from 

electrical resistivity imaging surveys in water-covered areas: 

Exploration Geophysics, v. 35, p. 266–271.

Malard, F., Plenet, S., and Gibert, J., 1996, The use of invertebrates in ground water monitoring—A rising research field: 

Ground Water Monitoring and Remediation, v. 16, no. 2, 

p. 103–113.

Malcolm, I.A., Soulsby, C., Youngson, A.F., and Petry, J., 

2003a, Heterogeneity in ground-water/surface-water 

interactions in the hyporheic zone of a salmonid spawning 

stream: Hydrological Processes, v. 17, p. 601–617.

Malcolm, I.A., Youngson, A.F., and Soulsby, Chris, 2003b, 

Survival of salmonid eggs in a degraded gravel-bed 

stream—Effects of ground-water/surface-water interactions: 

Hydrobiologia, v. 444, p. 303–316.

Manheim, F.T., Krantz, D.E., and Bratton, J.F., 2004, Studying 

ground water under Delmarva coastal bays using electrical 

resistivity: Ground Water, v. 42, no. 7, p. 1052–1068.

McBride, M.S., and Pfannkuch, H.O., 1975, The distribution 

of seepage within lakebeds: U.S. Geological Survey Journal 

of Research, v. 3, no. 5, p. 505–512.

McCarthy, K.A., McFarland, W.D., Wilkinson, W.D., and 

White, L.D., 1992, The dynamic relationship between 

ground water and the Columbia River—Using deuterium 

and oxygen-18 as tracers: Journal of Hydrology, v. 135, 

p. 1–12.

McLeod, R.S., 1980, The effects of using ground water 

to maintain water levels of Cedar Lake, Wisconsin: 

U.S. Geological Survey Water-Resources Investigations 

Report 80–23, 35 p.

Merritt, M.L., and Konikow, L.F., 2000, Documentation of 

a computer program to simulate lake-aquifer interaction 

using the MODFLOW Ground-Water Flow Model and the 

MOC3D Solute-Transport Model: U.S. Geological Survey 

Water-Resources Investigations Report 00–4167, 146 p.

Metz, P.A., and Sacks, L.A., 2002, Comparison of the hydrogeology and water quality of a ground-water augmented 

lake with two non-augmented lakes in northwest Hillsborough County, Florida: U.S. Geological Survey WaterResources Investigations Report 02–4032, 74 p.

Meyboom, P., 1966, Unsteady groundwater flow near a willow 

ring in hummocky moraine: Journal of Hydrology, v. 4, 

p. 38–62.

Meyboom, P., 1967, Mass-transfer studies to determine the 

groundwater regime of permanent lakes in hummocky 

moraine of western Canada: Journal of Hydrology, v. 5, 

p. 117–142.
Introduction and Characteristics of Flow 35

Miller, R.L., Kraemer, T.F., and McPherson, B.F., 1990, 

Radium and radon in Charlotte Harbor Estuary, Florida: 

Estuarine, Coastal and Shelf Science, v. 31, p. 439–457.

Mitchell-Bruker, S., and Haitjema, H.M., 1996, Modeling 

steady state conjunctive groundwater and surface water flow 

with analytic elements: Water Resources Research, v. 32, 

no. 9, p. 2725–2732.

Moore, W.S., 1996, Large groundwater inputs to coastal 

waters revealed by 226Ra enrichments: Nature, v. 380, 

p. 612–614.

Moore, W.S., 1999, The subterranean estuary—A reaction 

zone of ground water and sea water: Marine Geochemistry, 

v. 65, p. 111–125.

Moore, W.S., 2000, Determining coastal mixing rates using 

radium isotopes: Continental Shelf Research, v. 20, 

p. 1993–2007.

Mull, D.S., Liebermann, T.D., Smoot, J.L., and Woosley, 

L.H., Jr., 1988, Application of dye-tracing techniques for 

determining solute transport characteristics of ground water 

in karst terranes: U.S. Environmental Protection Agency 

Report 904/6–88–001.

Niswonger, R.G., and Prudic, D.E., 2005, Documentation of 

the streamflow-routing (SFR2) package to include unsaturated flow beneath streams—A modification to SFR1: 

U.S. Geological Survey Techniques and Methods 6–A13, 

48 p.

Niswonger, R.G., Markstrom, R.L., Regan, R.S., Prudic, D.E., 

Pohll, Greg, and Viger, R.J., 2006, Modeling ground-water/

surface-water interactions with GSFLOW, a new USGS 

model: Golden, Colo., Proceedings, MODFLOW and More 

2006, Managing Ground Water Systems, May 21–24, 2006, 

p. 99–103.

Oberg, K.A., Morlock, S.E., and Caldwell, W.S., 2005, 

Quality-assurance plan for discharge measurements using 

acoustic Doppler current profilers: U.S. Geological Survey 

Scientific Investigations Report 2005–5183, 44 p.

Orghidan, T., 1959, Ein neuer Lebensraum des unteriridischen 

Wassers: Der hyporheische Biotop: Archiv für Hydrobiologie, v. 55, p. 392–414.

Owen-Joyce, S.J., Wilson, R.P., Carpenter, M.C., and Fink, 

J.B., 2000, Method to identify wells that yield water that 

will be replaced by water from the Colorado River downstream from Laguna Dam in Arizona and California: 

U.S. Geological Survey Water-Resources Investigations 

Report 00–4085, 31 p. 19 maps.

Pfannkuch, H.O., and Winter, T.C., 1984, Effect of anisotropy 

and groundwater system geometry on seepage through 

lakebeds, 1, Analog and dimensional analysis: Journal of 

Hydrology, v. 75, p. 213–237.

Pluhowski, E.J., 1972, Hydrologic interpretations based on 

infrared imagery of Long Island, New York, Contributions 

to the hydrology of the United States: U.S. Geological Survey Water-Supply Paper 2009–B, 20 p.

Power, G., Brown, R.S., and Imhof, J.G., 1999, Groundwater 

and fish—Insights from northern North America: Hydrological Processes, v. 13, p. 401–422.

Prudic, D.E., 1989, Documentation of a computer program 

to simulate stream-aquifer relations using the modular 

finite-difference ground-water flow model: U.S. Geological 

Survey Open-File Report 88–729, 113 p.

Prudic, D.E., Konikow, L.F., and Banta, E.R., 2004, A new 

streamflow-routing (SFR1) package to simulate streamaquifer interaction with MODFLOW-2000: U.S. Geological 

Survey Open-File Report 2004–1042, 95 p.

Puckett, L.J., Cowdery, T.K., McMahon, P.B., Tornes, L.H., 

and Stoner, J.D., 2002, Using chemical, hydrologic, and age 

dating analysis to delineate redox processes and flow paths 

in the riparian zone of a glacial outwash aquifer-stream system: Water Resources Research, v. 38, no. 8, p. 9–1 to 9–20.

Rantz, S.E., and others, 1982a, Measurement and computation 

of streamflow—Volume 1, Measurement of stage and discharge: U.S. Geological Survey Water-Supply Paper 2175, 

284 p.

Rantz, S.E., and others, 1982b, Measurement and computation of streamflow—Volume 2, Computation of discharge: 

U.S. Geological Survey Water-Supply Paper 2175, 631 p.

Rimmer, Alon, and Gideon, Gal, 2003, Estimating the saline 

springs component in the solute and water balance of Lake 

Kinneret, Israel: Journal of Hydrology, v. 284, p. 228–243.

Robinove, C.J., 1965, Infrared photography and imagery in 

water resources research: Journal of the American Water 

Works Association, v. 57, pt. 2, p. 834–840.

Robinove, C.J., and Anderson, D.G., 1969, Some guidelines 

for remote sensing in hydrology: Water Resources Bulletin, 

v. 5, no. 2, p. 10–19.

Rosenberry, D.O., 1990, Inexpensive groundwater monitoring 

methods for determining hydrologic budgets of lakes and 

wetlands, in National Conference on Enhancing the States’ 

Lake and Wetland Management Programs: U.S. Environmental Protection Agency, North American Lake Management Society, p. 123–131. 

Rosenberry, D.O., 2005, Integrating seepage heterogeneity 

with the use of ganged seepage meters: Limnology and 

Oceanography/Methods, v. 3, p. 131–142.
36 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Rosenberry, D.O., Bukaveckas, P.A., Buso, D.C., Likens, G.E., 

Shapiro, A.M., and Winter, T.C., 1999, Migration of road 

salt to a small New Hampshire lake: Water Air and Soil Pollution, v. 109, p. 179–206.

Rosenberry, D.O., Striegl, R.G., and Hudson, D.C., 2000, Plants 

as indicators of focused ground water discharge to a northern 

Minnesota lake: Ground Water, v. 38, no. 2, p. 296–303.

Rosenberry, D.O., and Winter, T.C., 1997, Dynamics of watertable fluctuations in an upland between two prairie-pothole 

wetlands in North Dakota: Journal of Hydrology, v. 191, 

p. 266–289.

Rundquist, D., Murray, G., and Queen, L., 1985, Airborne thermal mapping of a “flow-through” lake in the Nebraska sandhills: Water Resources Research, v. 21, no. 6, p. 989–994.

Rutledge, A.T., 1992, Methods of using streamflow records for 

estimating total and effective recharge in the Appalachian 

Valley and Ridge, Piedmont, and Blue Ridge physiographic 

provinces: American Water Resource Association Monograph Series no. 17, p. 59–73.

Rutledge, A.T., 1998, Computer programs for describing the 

recession of ground-water discharge and for estimating 

mean ground-water recharge and discharge from streamflow 

data—Update: U.S. Geological Survey Water-Resources 

Investigations Report 98–4148, 44 p.

Rutledge, A.T., 2000, Considerations for use of the RORA 

program to estimate ground-water recharge from streamflow 

records: U.S. Geological Survey Open-File Report 2000–156, 

52 p.

Sacks, L.A., 2002, Estimating ground-water inflow to lakes 

in central Florida using the isotope mass-balance approach: 

U.S. Geological Survey Water-Resources Investigations 

Report 02–4192, 59 p.

Sacks, L.A., Swancar, Amy, and Lee, T.M., 1998, Estimating ground-water exchange with lakes using water-budget 

and chemical mass-balance approaches for ten lakes in 

ridge areas of Polk and Highlands Counties, Florida: 

U.S. Geological Survey Water-Resources Investigations 

Report 98–4133, 52 p.

Schindler, D.W., Newbury, R.W., Beaty, K.G., and Campbell, 

P., 1976, Natural water and chemical budgets for a small Precambrian lake basin in central Canada: Journal of the Fisheries Research Board of Canada, v. 33, no. 11, p. 2526–2543.

Sheets, R.A., Darner, R.A., and Whitteberry, B.L., 2002, Lag 

times of bank filtration at a well field, Cincinnati, Ohio, 

USA: Journal of Hydrology, v. 266, p. 162–174.

Simmons, G.M., Jr., 1992, Importance of submarine groundwater discharge (SGWD) and seawater cycling to material 

flux across sediment/water interfaces in marine environments: Marine Ecology Progress Series, v. 81, p. 173–184.

Simonds, F.W., and Sinclair, K.A., 2002, Surface-water/

ground-water interactions along the lower Dungeness River 

and vertical hydraulic conductivity of streambed sediments, 

Clallam County, Washington, September 1999–July 2001: 

U.S. Geological Survey Water-Resources Investigations 

Report 02–4161, 60 p.

Simonds, F.W., Longpre, C.I., and Justin, G.B., 2004, Groundwater system in the Chimacum Creek Basin and surfacewater/ground-water interaction in Chimacum and Tarboo 

Creeks and the Big and Little Quilcene Rivers, Eastern 

Jefferson County, Washington: U.S. Geological Survey Scientific Investigations Report 2004–5058, 60 p., one plate.

Smart, P.L., and Laidlaw, I.M.S., 1977, An evaluation of 

some fluorescent dyes for water tracing: Water Resources 

Research, v. 13, p. 15–33.

Sophocleous, Marios, 2002, Interactions between groundwater 

and surface water—The state of the science: Hydrogeology 

Journal, v. 10, p. 52–67.

Sophocleous, M.A., Koelliker, J.K., Govindaraju, R.S., Birdie, 

T., Ramireddygari, S.R., and Perkins, S.P., 1999, Integrated 

numerical modeling for basin-wide water management—

The case of the Rattlesnake Creek basin in south-central 

Kansas: Journal of Hydrology, v. 214, p. 179–196.

Sophocleous, Marios, and Perkins, S.P., 2000, Methodology and 

application of combined watershed and ground-water models 

in Kansas: Journal of Hydrology, v. 236, p. 185–201.

Steele, G.V., and Verstraeten, I.M., 1999, Effects of pumping 

collector wells on river—Aquifer interactions at Platte River 

Island near Ashland, Nebraska, 1998: U.S. Geological Survey Water-Resources Investigations Report 99–4161, 6 p.

Stewart, J.W., and Hughes, G.H., 1974, Hydrologic consequences of using groundwater to maintain lake levels 

affected by water wells near Tampa, Florida: Tallahassee, 

Florida, Bureau of Geology Report of Investigation, no. 74, 

41 p.

Stonestrom, D.A., and Constanz, Jim, eds., 2003, Heat as 

a tool for studying the movement of ground water near 

streams: U.S. Geological Survey Circular 1260, 105 p. 

(http://water.usgs.gov/pubs/circ/2003/circ1260/pdf/

Circ1260.pdf)

Strobel, M.L., Sawyer, J.F., and Rahn, P.H., 2000, Field trip 

road log—Hydrogeology of the central Black Hills of 

South Dakota, in Strobel, M.L., and others, eds., Hydrology of the Black Hills, Proceedings of the 1999 Conference 

on the Hydrology of the Black Hills: Rapid City, South 

Dakota School of Mines and Technology Bulletin no. 20, 

p. 239–245.

Stromberg, J.C., Tiller, R., and Richter, B., 1996, Effects of 

groundwater decline on riparian vegetation of semiarid 

regions—The San Pedro, Arizona: Ecological Applications, 

v. 6, no. 1, p. 113–131.
Introduction and Characteristics of Flow 37

Swain, E.D., and Wexler, E.J., 1996, A coupled surface-water 

and ground-water flow model (MODBRANCH) for simulation of stream-aquifer interaction: U.S. Geological Survey 

Techniques of Water-Resources Investigations, book 6, 

chap. A6, 125 p.

Squillace, P.J., Thurman, E.M., and Furlong, E.T., 1993, 

Groundwater as a nonpoint source of atrazine and deethylatrazine in a river during base flow conditions: Water 

Resources Research, v. 29, no. 6, p. 1719–1729.

Taniguchi, M., 1993, Evaluation of vertical groundwater 

fluxes and thermal properties of aquifers based on transient 

temperature-depth profiles: Water Resources Research, 

v. 29, no. 7, p. 2021–2026.

Taniguchi, Makato, Burnett, W.C., Cable, J.E., and Turner, 

J.V., 2002, Investigation of submarine groundwater discharge: Hydrological Processes, v. 16, p. 2115–2129.

Taniguchi, M., Ishitobi, T., and Shimada, J., 2006, Dynamics of submarine groundwater discharge and freshwaterseawater interface: Journal of Geophysical Research, v. 111, 

C01008, doi:10.1029/2005JC002924.

Taylor, J.I., and Stingelin, R.W., 1969, Infrared imaging for 

water resources studies: Journal of the Hydraulics Division, 

Proceedings of the American Society of Civil Engineers, 

v. 95, no. 1, p. 175–189.

Thoms, R.B., Johnson, R.L., and Healy, R.W., 2006, User’s 

guide to the Variably Saturated Flow (VSF) Process for 

MODFLOW: U.S. Geological Survey Techniques and 

Methods 6–A18, 58 p.

Vaccaro, J.J., and Maloy, K.J., 2006, A thermal profile method 

to identify potential ground-water discharge areas and preferred salmonid habitats for long river reaches: U.S. Geological Survey Scientific Investigations Report 2006–5136, 

16 p. (http://pubs.water.usgs.gov/sir2006-5136/)

Valiela, Ivan, Costa, Joseph, Foreman, Kenneth, Teal, 

J.M., Howes, Brian, and Aubrey, David, 1990, Transport 

of groundwater-borne nutrients from watersheds and 

their effects on coastal waters: Biogeochemistry, v. 10, 

p. 177–197.

Vanek, Vladimir, and Lee, D.R., 1991, Mapping submarine 

groundwater discharge areas—An example from Laholm 

Bay, southwest Sweden: Limnology and Oceanography, 

v. 36, no. 6, p. 1250–1262.

Wentz, D.A., Rose, W.J., and Webster, K.E., 1995, Long-term 

hydrologic and biogeochemical responses of a soft water 

seepage lake in north central Wisconsin: Water Resources 

Research, v. 31, no. 1, p. 199–212.

Wetzel, R.G., 1999, Plants and water in and adjacent to lakes, 

in Baird, A.J., and Wilby, R.L., eds., Eco-Hydrology: New 

York, Routledge, p. 269–299.

Winter, T.C., 1986, Effect of ground-water recharge on 

configuration of the water table beneath sand dunes and 

on seepage in lakes in the Sandhills of Nebraska, U.S.A.: 

Journal of Hydrology, v. 86, p. 221–237.

Winter, T.C., 1999, Relation of streams, lakes, and wetlands 

to groundwater flow systems: Hydrogeology Journal, v. 7, 

p. 28–45.

Winter, T.C., 2001, The concept of hydrologic landscapes: 

Journal of the American Water Resources Association, 

v. 37, no. 2, p. 335–349.

Winter, T.C., Harvey, J.W., Franke, O.L., and Alley, W.M., 

1998, Ground water and surface water a single resource: 

U.S. Geological Survey Circular 1139, 79 p.

Winter, T.C., LaBaugh, J.W., and Rosenberry, D.O., 1988, The 

design and use of a hydraulic potentiomanometer for direct 

measurement of differences in hydraulic head between 

groundwater and surface water: Limnology and Oceanography, v. 33, no. 5, p. 1209–1214.

Winter, T.C., and Rosenberry, D.O., 1995, The interaction of 

ground water with prairie pothole wetlands in the Cottonwood Lake area, east-central North Dakota, 1979–1990: 

Wetlands, v. 15, no. 3, p. 193–211.

Woessner, W.W., 1998, Changing views of stream-groundwater interaction, in Van Brahana, J., Eckstein, Y., Ongley, 

L.K., Schneider, R., and Moore, J.E., eds., Gambling with 

groundwater—Physical, chemical, and biological aspects of 

aquifer-stream relations: Las Vegas, Nev., Proceedings of 

the Joint Meeting of the XXVIII Congress of the International Association of Hydrogeologists and the annual meeting of the American Institute of Hydrologists, Las Vegas, 

Nevada, September 28 to October 2, 1998, p. 1–6.

Woessner, W.W., 2000, Stream and fluvial plain ground water 

interactions—Rescaling hydrogeologic thought: Ground 

Water, v. 38, no. 3, p. 423–429.

Woessner, W.W., and Sullivan, K.E., 1984, Results of seepage meter and mini-piezometer study, Lake Mead, Nevada: 

Ground Water, v. 22, no. 5, p. 561–568.

Zarriello, P.J., and Reis, K.G., III, 2000, A precipitation-runoff 

model for the analysis of the effects of water withdrawals 

on streamflow, Ipswich River Basin, Massachusetts: 

U.S. Geological Survey Water-Resources Investigations 

Report 00–4029, 99 p.

Zekster, I.S., 1996, Groundwater discharge into lakes—A 

review of recent studies with particular regard to large saline 

lakes in central Asia: International Journal of Salt Lake 

Research, v. 4, p. 233–249.

Use of Monitoring Wells, Portable 

Piezometers, and Seepage Meters 

to Quantify Flow Between Surface 

Water and Ground Water

By Donald O. Rosenberry, James W. LaBaugh, and Randall J. Hunt

Chapter 2 of

Field Techniques for Estimating Water Fluxes Between 

Surface Water and Ground Water

Edited by Donald O. Rosenberry and James W. LaBaugh

Techniques and Methods Chapter 4–D2

U.S. Department of the Interior

U.S. Geological Survey
Contents

Introduction...................................................................................................................................................43

Water-Level Measurements and Flow-Net Analysis.............................................................................43

Segmented Approach ........................................................................................................................43

Flow-Net Analysis...............................................................................................................................45

Sources of Error..................................................................................................................................47

Inadequate Physical Characterization...................................................................................47

Measurement Error...................................................................................................................48

Improperly Constructed Wells.................................................................................................48

Improperly Maintained Wells ..................................................................................................48

Unstable Wells and Staff Gages..............................................................................................49

Violation of Underlying Assumptions.............................................................................49

Hydraulic Potentiomanometer...................................................................................................................49

Sources of Error..................................................................................................................................51

Measurement Error...................................................................................................................51

Improper Leveling of the Manometer.....................................................................................51

Unstable Hydraulic Head..........................................................................................................51

Improper Seal Between Outer Pipe and the Sediments .....................................................51

Large Bubbles Entrained in Tubing.........................................................................................52

Leaks or Clogging.......................................................................................................................52

Waves, Standing Waves, and Seiches ..................................................................................52

Other Similar Devices.........................................................................................................................53

Cautions and Suggestions Related to Use of the Hydraulic Potentiomanometer ...................54

Seepage Meters...........................................................................................................................................54

Sources of Error..................................................................................................................................60

Incomplete Seal, Unstable Cylinder .......................................................................................60

Insufficient Equilibration Time .................................................................................................60

Improper Bag-Attachment Procedures, Bag Resistance, and Moving Water................60

Leaks. ...........................................................................................................................................63

Measurement Error...................................................................................................................63

Flexible Seepage-Meter Chamber..........................................................................................63

Insufficient or Excessive Bag-Attachment Time ..................................................................63

Accumulation of Trapped Gas ................................................................................................63

Use of Improper Correction Coefficient.................................................................................64

Insufficient Characterization of Spatial Heterogeneity in Seepage

Through Sediments ...............................................................................................................64

Best-Measurement Practices for Manual Seepage Meters ....................................65

Automated Seepage Devices ...........................................................................................................66

Methods Selection..............................................................................................................................66

References....................................................................................................................................................67
Figures

1. A hypothetical lake segmented based on positioning of near-shore watertable wells....................................................................................................................................44

2. Typical hydraulic conditions in the vicinity of the shoreline of a surfacewater body ...................................................................................................................................44

3. A flow net generated to indicate flow of water to and from a hypothetical lake ............46

4. Conceptualization of flow based on flow-net analysis and segmented 

Darcy fluxes.................................................................................................................................47

5. Hydraulic potentiomanometer showing drive probe inserted into lakebed 

and manometer indicating a very small vertical hydraulic-head gradient.......................49

6. Diagram of components of the hydraulic potentiomanometer system .............................50

7. Hydraulic potentiomanometer designed to place the manometer tubes connected 

to the drive probe and to the surface-water body close together to minimize outof-level errors..............................................................................................................................52

8. Hydraulic potentiomanometer probe with drive hammer shown driven about 

2 meters beneath the lakebed ..................................................................................................53

9. Photograph showing hydraulic potentiomanometer............................................................54

10. Photograph showing portable well probe consisting of a commercially available 

retractable soil-gas vapor probe connected to threaded pipe with tubing inside

the pipe connected to the vapor probe...................................................................................55

11. Diagram showing well probe constructed from a commercially available root 

feeder with the coiled tubing substituting for a manometer...............................................55

12. MHE PP27 probe used to indicate difference in head..........................................................56

13. A, Half-barrel seepage meter, B, standard half-barrel seepage meter in place 

in the field, and C, electromagnetic seepage meter installed next to a half-barrel 

seepage meter ............................................................................................................................57

14. Seepage meter modified for use in large lakes.....................................................................58

15. Ground-water seepage meter modified for use in deep water ..........................................59

16. Plastic bag attached to a garden-hose shut-off valve.........................................................62

17. Resistance to flow related to tubing diameter and rate of seepage..................................64

18. Seepage flux measured at two seepage meters located 1 meter apart...........................65

Tables

1. Data for calculating flows to and from the lake shown in figure 1, and total 

flow per segment (Q), using the segmented Darcy approach ............................................45

2. Duration between emplacement of seepage meter and first installation of 

seepage-meter bag (equilibration time) from selected studies..........................................61

3. Seepage flux with distance from shore and distance along shore on an 

8-meter by 8-meter grid (2-meter seepage-meter spacing) ...............................................66

4. Conditions for which methods for quantifying flow between ground water 

and surface water are well- or ill-suited ................................................................................67

Introduction

This chapter describes three of the most commonly used 

methods to either calculate or directly measure flow of water 

between surface-water bodies and the ground-water domain. 

The first method involves measurement of water levels in a 

network of wells in combination with measurement of the 

stage of the surface-water body to calculate gradients and then 

water flow. The second method involves the use of portable 

piezometers (wells) or hydraulic potentiomanometers to measure gradients. In the third method, seepage meters are used 

to measure directly flow across the sediment-water interface 

at the bottom of the surface-water body. Factors that affect 

measurement scale, accuracy, sources of error in using each of 

the methods, common problems and mistakes in applying the 

methods, and conditions under which each method is well- or 

ill-suited also are described.

Water-Level Measurements 

and Flow-Net Analysis

The flow-net analysis method, often called the “Darcy 

approach,” is probably the most frequently used method for 

quantifying flow between ground water and surface water, 

especially on a whole-lake or watershed scale. In this method, 

a combination of measurements of water levels in near-shore 

water-table wells and measurements of water stage of adjacent 

surface-water bodies are used to calculate water-table gradients 

between the wells and the surface-water body. Two approaches 

commonly are used. One approach segments the shoreline of the 

surface-water body, depending on the number and location of 

nearby wells. The second approach generates equipotential lines 

based on hydraulic-head and surface-water stage data, and uses 

flow-net analysis to calculate flows to and from the surface-water 

body. Both methods are described in the following section.

Values of hydraulic conductivity (K), which also are 

needed to quantify flow, commonly are determined from 

single-well slug tests conducted in the same wells in which 

water levels are measured to calculate hydraulic gradients 

(although a multiple-well aquifer test that encompasses a 

large volume of aquifer often provides a better indication 

of hydraulic conductivity appropriate to a lake or watershed 

scale). Spatial resolution of hydraulic-head gradients and flow 

between ground water and surface water is directly related 

to geologic heterogeneity; the greater the heterogeneity of 

an aquifer, the larger the number of data points (wells) that 

will be needed to accurately determine hydraulic conditions. 

Heterogeneity often is difficult to determine in practice, and in 

many instances, ranges of reasonable values for K are used to 

estimate the range of flows.

Segmented Approach

In this approach, the shoreline of a surface-water body 

is divided into segments, with the number of segments 

depending on the location and number of nearby monitoring wells (fig. 1). For each shoreline segment and associated 

well, hydraulic conductivity and the gradient between the well 

and the surface-water body are applied to the entire segment. 

The length of the shoreline segment, m, is multiplied by the 

effective thickness of the aquifer, b, to determine the area, A, 

of a vertical plane at the shoreline through which water passes 

to either enter or leave the surface-water body (fig. 2). The 

Darcy equation commonly is used to calculate the flow of 

water that passes through the vertical plane associated with 

each segment:

Q KA h h

L  ( ) 1 2 
 , (1)

where

Q is flow through a vertical plane that extends 

beneath the shoreline of a surface-water 

body (L3

/T);

K is horizontal hydraulic conductivity (L/T);

A is the area of the plane through which all 

water must pass to either enter or leave 

the surface-water body, depending on the 

direction of flow [shoreline length (m) ×

effective thickness of the aquifer (b)] (L2

);

h1 is hydraulic head in the well of interest (L);

h2 is surface-water stage (L);

and

L is distance from the well to the shoreline (L).

Chapter 2

Use of Monitoring Wells, Portable Piezometers, and 

Seepage Meters to Quantify Flow Between Surface 

Water and Ground Water

By Donald O. Rosenberry, James W. LaBaugh, and Randall J. Hunt
44 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Flows to or from the surface-water body are summed 

to calculate net flow for the entire surface-water body. This 

method assumes that:

1. All water that exchanges with a surface-water body 

passes horizontally through a vertical plane positioned 

at the shoreline that extends to a finite depth (b) beneath 

the surface of the surface-water body. At depths greater 

than b, ground water flows beneath the surface-water 

body and does not exchange with the surface-water body;

2. The direction of water flow is perpendicular to the shoreline as flow enters or leaves the surface-water body;

3. The gradient (water-table slope) between the well and 

the surface-water body is uniform; and

4. The aquifer is homogeneous and isotropic within 

the segment.

Although the Darcy equation is most commonly used in 

calculating flows between ground water and surface water, its 

assumption of a constant aquifer thickness is violated where 

the water table slopes in the vicinity of a surface-water body. 

In these near-shore, unconfined aquifer settings, the use of the 

Dupuit equation may be more appropriate because it allows 

the sloping ground-water table to be the upper boundary of the 

ground-water domain. The Dupuit equation can be written as:

Q Km h h

L  ( ) 1 
2

2

2

2

, (2)

where

h1 = aquifer thickness at the well,

and

h2 = aquifer thickness at the edge of the surfacewater body.

The Dupuit equation assumptions are:

1. The sediments are homogeneous and isotropic;

2. Flow in the aquifer is parallel to the slope of the water 

table; and

3. For small water-table gradients, ground-water flow lines 

(also called streamlines) are horizontal.

These assumptions require that equipotential lines (lines 

of equal hydraulic head) are perpendicular to the ground-water 

flow lines and are vertical.

As indicated in figure 2, near the shoreline, where 

water-table gradients typically steepen, these assumptions are 

violated to some degree. If flow is parallel to the water table, 

and the water-table gradient is sufficiently steep, then flow 

in the ground-water system obviously cannot be horizontal. 

Errors that result from violating these assumptions typically 

are minor relative to the uncertainty in determining K.

Another source of uncertainty in applying the Dupuit 

equation is the determination of h1 and h2

. As with use of the 

Darcy equation, h1

 and h2 should include only ground-water 

Well

Lake

97

97

70

78

80

72

61

70

75

650

500

430

550

850

600

800

200

400

425

300

275

350

225

A

A

B

C

D

E

F

G

EXPLANATION

Well location and ground-water level

Watershed segment boundary

Watershed segment designation

Distance from well to shoreline, in meters

Shoreline length per watershed segment,

 in meters

425

500

0

0

1,000 METERS

3,000 FEET

200 400 600 800

1,000 2,000

Figure 1. A hypothetical lake segmented based on positioning 

of near-shore water-table wells. Values are hydraulic head and 

surface-water stage.

Figure 2. Typical hydraulic conditions in the vicinity of the shoreline 

of a surface-water body. (Artwork by Donald O. Rosenberry.)

A

Ground-water flow lines

b

m Break in

slope

Water-table well

Surface-water

body Shoreline segment

L

Flow passes beneath lake and is outside of local-flow domain
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 45

flow lines that intersect the surface-water body and exclude 

those flow lines that pass beneath the surface-water body, 

in which case h2

 = b as shown in figure 2. This is especially 

important in cases where a lake, stream, or wetland occupies 

only the shallow, surficial part of a thick aquifer. As discussed 

later, h2

 or b often is one of the more difficult parameters 

to determine.

Although the use of the Dupuit equation is more appropriate for unconfined aquifer settings, the error that results 

from using the Darcy equation instead of the Dupuit equation 

commonly is small relative to the uncertainty in determining 

K. For a small water-table gradient, the errors are very small, 

and errors are small even for a relatively large water-table 

gradient. For example, assuming a large water-table gradient 

of 0.1 and the following values for a 1-meter shoreline reach 

(h1 = 60 meters, h2 = 50 meters, L = 100 meters, K = 10 meters 

per day), the Dupuit flow (Q) = 55 cubic meters per day, and 

the Darcy flow (Q ) = 50 cubic meters per day.

An example of the use of the Darcy approach to calculate 

flows to and from a surface-water body using values obtained 

from figure 1 is shown in table 1. The example assumes that K

is 30 meters per day and is uniform throughout the watershed, 

and that b is 20 meters. The method assumes that the hinge 

lines, the locations where flow direction changes from flow 

into the lake to flow out of the lake, occur at the ends of the 

adjacent shoreline segments where a change in flow direction 

is indicated. Considering the uncertainty associated with positioning of the hinge lines, the difference between total flow 

into the lake and total flow out of the lake is remarkably small 

in this example.

Flow-Net Analysis

The flow-net analysis is a graphical method for solving 

steady-state two-dimensional ground-water flow. The analysis 

uses the Darcy equation to solve for flow, the distribution of 

which is dependent on the flow net that is generated manually 

or with computer software. The method assumes that steadystate flow is two-dimensional (either in plan view, as applied 

here, or along a cross section), the aquifer is homogeneous 

and isotropic, and that b (the effective thickness of the aquifer) is known. Rules regarding construction of flow nets are 

described in Fetter (2000) and in other hydrogeology texts (for 

example, Davis and DeWiest, 1991). A detailed analysis of the 

method is provided in Cedergren (1997). In brief, the flow net 

consists of equipotential lines (lines of equal hydraulic head) 

and flow lines (also called streamlines). Equipotential lines are 

drawn on the basis of hydraulic head in the wells and the stage 

of the surface-water body. They intersect no-flow boundaries 

at right angles. Assuming the porous medium is homogeneous 

and isotropic, flow lines are drawn perpendicular to the equipotential lines. A sufficient number of flow lines are drawn so 

that the resulting rectilinear shapes form approximate squares. 

The areas between the flow lines are called streamtubes. 

The intervals between equipotential lines are termed “head 

drops.” Once the flow net is constructed, a form of the Darcy 

equation is used to approximate flow to or from the surfacewater body:

Q MKbH

n  , (3)

where

M = the number of streamtubes across a 

flow net,

H = total head drop across the area of 

interest (L),

n = number of equipotential head drops over 

the area of interest, and Q, K, and b are 

as defined previously.

An example of the flow-net approach is shown in 

figure 3. The flow net is created using the same hypothetical 

setting shown in figure 1. The flow domain has been rotated 

Table 1. Data for calculating flows to and from the lake shown in figure 1, and total flow per segment (Q), using the segmented 

Darcy approach.

[m/d, meters per day; m, meter; m3/d, cubic meters per day]

Watershed 

segment

Horizontal hydraulic

conductivity (K) 

(m/d)

Effective thickness

of the aquifer (b)

(m)

Hydraulic head

in well—surfacewater stage (h1

–h2)

(m)

Distance from 

the well to the 

shoreline (L)

(m)

Length of shoreline

segment (m)

(m)

Water flow (Q)

(m3

/d)

A 30 20 22 425 500 15,529

B 30 20 5 200 650 9,750

C 30 20 –3 225 550 –4,400

D 30 20 –14 350 430 –10,320

E 30 20 –5 275 800 –8,727

F 30 20 –5 300 600 –6,000

G 30 20 3 400 850 3,825

Total flow into lake = 29,104 cubic meters per day.

Total flow out of lake = 29,447 cubic meters per day.
46 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

so that equipotential lines are approximately perpendicular to the no-flow boundaries on the top and bottom of the 

figure, and streamlines are approximately perpendicular to 

constant-head boundaries to the left and right of the figure. 

The equipotential lines represent hydraulic-head intervals of 

10 meters. The total flow of water that exchanges with the lake 

is apportioned into seven streamtubes. Using the same values 

for K, b, hydraulic head, and lake stage as for the segmented 

Darcy method, and values of 7, 35, and 3.5 for M, H, and n, 

respectively, the total Q into the lake is 42,000 cubic meters 

per day. Total Q out of the lake, based on the same values 

as for the segmented Darcy method of 7, 15, and 1.5 for M, 

H, and n, respectively, also is 42,000 cubic meters per day. 

These values are substantially larger (44 percent) than total 

flows into and out of the lake calculated by the segmented 

Darcy method.

A comparison of results from the two methods indicates 

the relative accuracy of these methods. Substantial errors 

can result with the segmented Darcy method if conditions 

along each shoreline segments are not uniform. For example, 

determination of flow across the curving segment on the 

northwest side of the lake assumes that an arc of hydraulic 

head 22 meters higher than the lake surface exists a distance 

of 425 meters from shore along the entire shoreline segment. 

Common sense and the flow-net analysis (fig. 3) indicate that 

0

0

1,000 METERS

3,000 FEET

200 400 600 800

1,000 2,000

Well

97

70

78

80

72

70

80

90

110

100

70

1

1

2

3

4

0.5

0.5

2 1

3

1

5

6

7

2

3

4

5

6

7

1

0.5

EXPLANATION

Equipotential line

Flow line

Streamtube number

Equipotential head drop 

97 Well location and ground-water level

Hinge line

Lake

60

61

70

75

Figure 3. A flow net generated to indicate flow of water to and 

from a hypothetical lake. Ground-water flow direction is indicated 

by flow lines (blue lines), and lines of equal hydraulic head 

(equipotential lines) are shown with dashed lines. Values shown 

are hydraulic head in the wells and surface-water stage.

this is a poor assumption. Also, incorrect placement of the 

hinge-line location can result in shoreline segments drawn 

adjacent to the hinge line that poorly represent the actual local 

flow into and out of the surface-water feature. Figure 4 shows 

the flow lines drawn in figure 3 in addition to the shoreline 

segments indicated in figure 1. Positioning of hinge lines in 

figure 4 is based on the flow-net analysis. If the segmented 

Darcy method was used to place hinge lines, they would be 

located at the boundaries between segments B and C, and 

between segments F and G. Fortunately, a misplacement of 

the hinge line commonly does not result in substantial error 

because flow across the sediment-water interface commonly 

is small where ground-water flow is primarily parallel to 

the shoreline.

The flow-net analysis method provides a simple, initial 

estimate of the exchange of water between a surface-water 

body and ground water. The accuracy of the method depends 

on the degree to which the simplifying assumptions are met 

in the setting being analyzed and on how well the mesh 

is drawn. Errors can be minimized by ensuring that areas 

contained by the streamtubes and equipotential lines form 

approximate squares. Cedergren (1997) provides additional 

information for minimizing mesh-related errors. Uncertainties associated with accurate representation of K commonly 

are significantly larger than errors associated with improperly 

constructed flow-net meshes. With a larger number of wells, 

equipotential lines can be placed more precisely and a finer 

grid then can be generated. Accuracy also depends on how 

the flow net is interpreted. For example, in the setting shown 

in figure 3, streamtubes that partly intersect the lake were 

ignored. Those streamtubes might instead have been considered as half streamtubes, in which case the total flow into and 

out of the lake would have been larger. Alternately, streamtubes 1 and 7 could have been drawn so as to bypass the lake, 

in which case only five streamtubes would intersect the lake. If 

the number of streamtubes was five instead of seven, the flownet-derived fluxes to and from the lake (30,000 cubic meters 

per day) would be nearly identical to the segmented Darcygenerated fluxes.

The domain shown in figure 3, although rotated to be 

aligned with flow lines and equipotential lines, was drawn 

with the same dimensions as the domain shown in figure 1. 

One could argue, however, that the domain should have been 

made larger because many of the flow lines and equipotential 

lines do not intersect the boundaries at right angles.
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 47

Sources of Error

Sources of error in applying the segmented-shore or flownet-analysis approach to the determination of the exchanges 

between a surface-water body and ground water, in addition to 

errors in interpretation presented above, include:

1. Inadequate physical characterization of conditions or 

properties that affect flow,

2. Measurement error,

3. Improperly constructed wells,

4. Improperly maintained wells,

5. Unstable wells and stage gage, and

6. Violation of underlying assumptions.

Each item is discussed in detail below.

Inadequate Physical Characterization

In the examples given above, horizontal hydraulic 

conductivity (K) was assumed to be uniform across the entire 

watershed. This is a poor assumption because erosional and 

depositional conditions near the shoreline commonly are different than for the larger watershed. Where lower-K sediments 

line lakes or wetlands, K within a meter of the sediment-water 

interface can be the dominant control on flow (Rosenberry, 

2000). This is especially well documented in fluvial settings 

(for example, Brunke, 1999; Hiscock and Grischek, 2002; 

Schubert, 2002; Sheets and others, 2002; Fleckenstein and 

others, 2006). It usually is beneficial to install additional wells 

near the shoreline of the surface-water body to gain a better 

understanding of the distribution of hydraulic head and of the 

spatial variability in K.

A slug test can be expected to provide only an approximate estimate of the actual K that controls flow between 

ground water and surface water. First, slug tests measure 

horizontal K, but aquifers commonly are anisotropic; vertical 

K typically is smaller, sometimes orders of magnitude smaller, 

than horizontal K. Second, measurements of K are to some 

extent scale dependent and single-well slug tests may provide 

values that are too small to be representative of the larger scale 

flow in the aquifer. Rovey and Cherkauer (1995) found that 

K of a carbonate aquifer in Wisconsin increases linearly with 

the scale of the measurement up to a radius of influence of 

between 20 and 220 meters, after which point K was constant 

with increasing radius. Schulze-Makuch and others (1999) 

indicated that scale dependence of K depends on the hydraulic properties of an aquifer. They reported that K is relatively 

insensitive to scale for homogeneous aquifers but increases 

by half an order of magnitude for every order of magnitude 

increase in spatial scale of heterogeneous aquifers. Unless the 

well is installed in the lake, the approaches outlined herein do 

not attempt to quantify exchange between ground water and 

surface water at the surface-water feature itself. Rather, they 

estimate the flow into and out of the ground-water system 

near the surface-water feature, at the locations of the monitoring wells and assume that water that crosses the vertical 

plane at the shoreline must either originate from or flow into 

the lake.

Determination of the effective thickness of the aquifer 

(b) through which water flows to interact with a surfacewater body also can be difficult. Investigators may resort to 

hypothetical flow modeling or to tracers to address this issue. 

Siegel and Winter (1980) and Krabbenhoft and Anderson 

(1986) used finite-difference ground-water flow models to 

estimate the part of an unconfined aquifer that interacts with 

a lake. Taniguchi (2001) used a one-dimensional advectiondispersion model calibrated to chloride data to determine that 

b for Lake Biwa, Japan, was 150 meters. Lee and Swancar 

(1997) used vertical ground-water flow divides to determine 

b for their flow-net analysis for a lake in Florida. Perhaps the 

most thorough investigation to date is a study of flow between 

two lakes in northern Wisconsin. Flow-net, isotopic and geochemical, and numerical modeling approaches have been used 

to determine the relative volumes of water that flow from the 

upgradient lake to the downgradient lake and water that flows 

from the upgradient lake, beneath, and ultimately beyond the 

downgradient lake (for example, Kim and others, 1999).

Conceptual models of hypothetical settings can be useful 

in constraining estimates of exchange between ground water 

and surface water when sufficient field data are not available. 

Simply knowing the size, shape, and depth of a lake relative to 

its watershed can aid in determining the degree of interaction 

Figure 4. Conceptualization of flow based on flow-net analysis 

and segmented Darcy fluxes. The position of the hinge line 

changes depending on the method of analysis used.

Hinge line

Well

Lake

97

75

70

78

80

72

61

70

G

F

E

D

C

B A
48 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

between the lake and its watershed. Two-dimensional and 

three-dimensional numerical and analytical tools can visually present the types and relative scales of flow paths associated with exchange between ground water and surface 

water (Townley and Davidson, 1988; Nield and others, 1994; 

Townley and Trefry, 2000). Recent updates of ground-water 

flow models allow more realistic simulation of exchanges 

between ground water and surface water than was previously possible. Hunt and others (2003) provide an overview 

of the usefulness of these improvements associated with the 

U.S. Geological Survey MODFLOW model (Leake, 1997; 

Harbaugh and others, 2000; Harbaugh, 2005).

Compared to errors associated with conceptualizing 

flow paths and determining aquifer properties, the remaining 

sources of error listed here usually are relatively minor. They 

are included, however, for completeness, and because in some 

situations they can represent a significant part of the total error 

associated with quantifying flow between ground water and 

surface water.

Measurement Error

Errors in making water-level measurements in wells and 

in observing surface-water stage generally are not significant 

relative to errors in determining K or A. Errors associated with 

determining the elevation of the top of the well casing relative to surface-water stage also typically are small. Increasing 

accuracy and availability of global positioning systems are 

reducing errors associated with determining well location. 

These errors can be significant, however, if the well is within a 

few meters of the surface-water body or if hydraulic gradients 

are very small. In this instance, greater care and more accurate 

methods should be used in determining the position of the well 

and the elevation of the top of the well casing relative to the 

surface-water stage.

Improperly Constructed Wells

Water-table wells in which water levels will be measured 

to calculate fluxes between ground water and surface water 

should be constructed so the water level in the well represents the phreatic surface of the aquifer (the water table). The 

screened interval of the well should be placed so it intersects 

the water table over the expected range of water-table fluctuations. Typical well-screen lengths for water-table monitoring 

wells range from 0.3 to 3 meters. Wells with long screens will 

integrate hydraulic head over the length of the well screen, and 

wells with short screens that are placed substantially below the 

water table will provide hydraulic head at depth in the aquifer 

that may be considerably different from the water-table head, 

especially within two to three aquifer thicknesses from the 

lake (Hunt and others, 2003).

Improper well construction also can alter hydrologic 

representation, particularly if the completion method results in 

the well screen being isolated from the aquifer. If drilling mud 

is used during well construction, for example, the well must 

be sufficiently developed following completion of the drilling 

to ensure that the well is in good hydraulic connection with 

the aquifer. For wells that are driven or pounded to the desired 

depth, a common installation method near the shoreline where 

the depth to water is shallow, care also needs to be given 

to proper development of the well. Well screens often are 

smeared with fine-grained sediment during the driving process 

and can be completely clogged if they are not flushed following installation. Hand-augered wells commonly are installed 

with the bottom of the well screen a short distance below the 

water table. It is difficult to auger through sand much beyond 

1 meter below the water table because the sand collapses into 

the part of the hole below the water table. The consequence of 

the water table dropping below the bottom of the well screen is 

a dry well. A word of caution is in order for water-level measurements in wells constructed so the screen does not extend 

all the way to the well bottom (that is, when an impervious 

cap or drive point extends beyond the bottom of the screen); 

a small amount of water can be trapped inside the cap or 

drive point and remain in the well even if the water table has 

dropped below the bottom of the well. In such instances, the 

observer can still make a water-level measurement in the well 

and may not realize that the actual water table is below the 

bottom of the well.

The well screen also needs to be selected with a slot size 

(width of the openings in the screen) that is appropriate for 

the geologic material in which the screen is installed. If the 

slot size is too small, water levels in the well will lag behind 

changes in hydraulic head in the aquifer (Hvorslev, 1951). 

If the slot size is too large, particles will pass through the 

screen and may fill the well bore. Improper slot size may not 

be important when monitoring water levels on a weekly or 

less frequent interval, but can be very important if water-level 

change is recorded as part of a slug test or aquifer test.

Improperly Maintained Wells

Water-table monitoring wells can become clogged with 

sediments or bacterial growth, in part because so little water 

typically flows through a monitoring-well screen. Chemical 

precipitates (scale) also can clog the openings of a well screen. 

These processes decrease the connectivity of the well with the 

aquifer, creating a delayed response between the water level 

in the well and the hydraulic head in the aquifer. In extreme 

instances, the water level in the well becomes unresponsive to 

temporal changes in aquifer hydraulic head. Monitoring wells 

should be flushed occasionally to test and maintain connectivity with the aquifer.

The top of the well casing is vulnerable to accidental 

damage or vandalism. Protective devices for wells should be 

maintained and records kept in order to document any changes 

in the elevation of the top of the well casing to which water 

levels in the well typically are referenced.
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 49

Unstable Wells and Staff Gages

Water-table monitoring wells located near surface-water 

bodies commonly are quite shallow because the depth to the 

water table is shallow. Shallow well casings can move vertically in response to pumping for water-sample collection, 

frost, and settling of well cuttings placed in the annular space 

between the well casing and undisturbed sediments. This is 

particularly common for wells installed in wetland sediments. 

Shallow wells constructed with plastic casing can break from 

ice expansion during subfreezing temperatures. Wells and 

surface-water staff gages located near a downwind shoreline 

also can be tilted, moved horizontally, or broken if surface ice 

is pushed onto the shoreline during fall freeze or spring thaw. 

For longer term studies, it may be cost effective to install a 

sturdy surface-water monitoring station so that sources of 

environmental damage are minimized (Buchanan and Somers, 

1982). A less expensive means for obtaining greater stability 

in a surface-water stage record is the installation of a siphon 

gage that allows measurement of surface-water stage in a 

protected environment (McCobb and others, 1999). Annual 

leveling surveys are necessary for surface-water staff gages, as 

well as many near-shore wells, in order to document changes 

in the elevation of the staff gage or the top of the well casing. Multiple survey benchmarks can aid in maintaining 

long-term elevational accuracy for staff gages and shallow, 

near-shore wells.

Violation of Underlying Assumptions

The previously discussed assumptions of homogeneity and isotropy, inherent in most calculations of exchange 

between ground water and surface water, are rarely met or 

appropriate for near-shore settings and can result in large 

errors in quantifying exchange between ground water and 

surface water. Assumptions of two-dimensional areal flow 

also typically are violated in near-shore regions (two to three 

aquifer thicknesses from the surface-water feature) where 

convergences and divergences of flow lines are common. The 

Darcy approach also assumes that the system is in a steadystate condition. Although the natural world is rarely if ever 

at true steady state, the system often will have periods when 

water levels are not changing appreciably over time, during 

which representative estimations of average flows can be 

made. It often is instructive to construct a simple computer 

model of the physical hydrologic setting, even if the entire 

hydrogeologic framework is not adequately known. Such a 

tool facilitates testing of the significance of one or more of 

these assumptions. In addition, a preliminary model can be 

used to help identify sensitive parameters and locate areas 

in the watershed where additional data collection would be 

most beneficial.

Hydraulic Potentiomanometer

The hydraulic potentiomanometer, sometimes referred to 

as a mini-piezometer, is a portable drive probe connected to 

a manometer (fig. 5). The manometer provides a comparison 

between the stage of a surface-water body and the hydraulic 

head beneath the surface-water body at the depth to which the 

screen at the end of the probe is driven (Winter and others, 

1988). The difference in head divided by the distance between 

the screen and the sediment-water interface is a measurement 

of the vertical hydraulic-head gradient. By driving the probe 

to different depths beneath the sediment-water interface, the 

probe can provide information about variability in vertical 

hydraulic-head gradient with depth. The device does not give 

a direct indication of seepage flux, but when used in combination with a seepage meter, which does measure water flux, the 

two devices can yield information about the hydraulic conductivity of the sediments (for example, Kelly and Murdoch, 

2003; Zamora, 2006). Because this device provides a quick 

characterization of the direction and magnitude of the vertical hydraulic gradient, it is useful as a reconnaissance tool in 

lakes, wetlands, and streams. It also is useful in areas where 

near-shore water-table wells or piezometers do not exist, are 

sparsely distributed, or are impractical to install and maintain.

The original hydraulic potentiomanometer design 

(fig. 6) consists of two nested stainless-steel pipes separated 

by O-rings that rest in grooves machined into the inner pipe. 

A screen with a machined point is threaded onto the inner 

pipe. The outer pipe acts as a shield for the screen; it covers 

Figure 5. Hydraulic potentiomanometer showing drive probe inserted 

into lakebed and manometer indicating a very small vertical hydraulichead gradient (blue arrows indicate water levels on manometer). 

(Photograph by Donald Rosenberry, U.S. Geological Survey.)
50 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

the screen and prevents damage to the screen and smearing 

of fine-grained sediments during insertion of the probe. A 

manometer is connected to the probe to allow measurement of 

the difference between head at the exposed well screen and the 

stage of the surface-water body.

Once the probe is pushed to a desired depth beneath the 

sediment-water interface, the outer pipe is retracted to expose 

the screen. At this point, one could simply measure from the 

top of the well pipe to the water level inside the probe and 

to the surface-water level outside of the probe. The difference between these measurements is the head difference. For 

convenience, and to better resolve small head differences, a 

manometer is attached to the probe. A vacuum is applied at the 

top of the manometer, pulling water through tubing connected 

to the probe and the surface water. Greater resistance of flow 

through the well screen may require that the surface-water 

tube be clamped to allow development of sufficient suction to 

pull water through the well screen and tubing. When all of the 

tubing is full of water and free of bubbles, air is bled into the 

top of the manometer until the menisci are visible in the tubing on both sides of the manometer (fig. 5). The difference in 

height of the menisci equals the difference between head at the 

screen in the sediment and the stage of the surface-water body.

The hydraulic potentiomanometer works well in fine 

sands and coarser materials. It becomes difficult to pull 

water through the screen if the sediments contain significant 

amounts of silt, clay, or organic deposits. The probe is 

difficult to insert in rocky or cobbly sediments because of 

the difficulty of driving the probe past the rocks and also 

because it is difficult to obtain a good seal between the outer 

pipe of the probe and the sediments. Rocks and cobbles near 

the shoreline often are only a surficial veneer; however, a 

measurement usually is possible if the probe can penetrate 

the surface layer.

Variability in the direction and magnitude of horizontal hydraulic-head gradient with distance from shore can be 

determined by making measurements along transects oriented 

perpendicular to the shoreline. The probe should be inserted to 

the same depth beneath the sediment-water interface at each 

measurement location. Otherwise, it is impossible to distinguish spatial variability in horizontal gradients from spatial 

variability in vertical gradients. One end of each transect typically extends to the shoreline, but measurements also can be 

made onshore in places where the probe can be driven deeply 

enough to reach the water table. For onshore measurements, 

the hydraulic potentiomanometer probe provides data equivalent to that of a shallow, near-shore monitoring well, while 

the tubing in the lake serves as a surface-water gage. Where 

the near-shore land-surface slope is small, the probe can be 

inserted a considerable distance from the shoreline, although 

the tubing needs to be long enough to extend from the well 

probe to the surface-water body. The vertical distribution of 

vertical hydraulic-head gradients can be determined by driving 

the probe to multiple depths beneath the sediment-water interface at each measurement location. This provides information 

about geologic heterogeneity with depth beneath the sedimentwater interface, which can have a large influence on depthintegrated hydraulic-head gradients. In rivers, it is common 

for sediments to be composed of alternating layers of organic 

and inorganic sediments or fine-grained and coarse-grained 

sediments. Measurements often cannot be made in the organic 

or fine-grained layers, in which case measurements should be 

attempted in the more permeable layers. Differences in head 

between the transmissive layers often are large because the 

intervening low-permeability layers limit the equalization of 

pressure between the transmissive layers. Biogenic gas, which 

is common in many riverine sediments, can make obtaining 

bubble-free measurements difficult.

Differences in hydraulic head, although dependent on the 

depth to which the probe is inserted, typically range from 0 to 

10 centimeters, but head differences as much as 30 centimeters 

are not uncommon. In some settings, the head difference can 

be very large, primarily because of local-scale geologic heterogeneity. In rare instances, head differences are greater than the 

length of the manometer, in which case the manometer can be 

raised, allowing the lower-head meniscus to be situated in the 

clear flexible tubing connected to the base of the manometer. 

For example, a head difference of approximately 2.4 meters 

was reported at a site where water was flowing from a lake to 

ground water (Rosenberry, 2000). The extreme gradient was 

present because a nearby lake had a water level 14 meters 

lower than the upper lake. Coarse sand was present between 

the two lakes, and much of the head difference between the 

two lakes was distributed across a 20-centimeter-thick layer 

Figure 6. Components of the hydraulic potentiomanometer 

system. (Modified from Winter and others, 1988; copyright 1988 by 

the American Society of Limnology and Oceanography, Inc., used 

with permission.)

Probe

Manometer

board

Tube A

Tube C Valve

Valve or 

clamp

Pump

To optional

sample bottle

Water 

surface

Tube B

Filter

Lake bed
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 51

of organic-rich, sandy sediment at the sediment-water interface 

of the upper lake. Although still quite permeable compared to 

other lake sediments in the area, the permeability of the top 

20 centimeters of sandy lake sediment was one to two orders 

of magnitude lower than that of the underlying coarse sand. 

The manometer had to be raised well above the lake surface 

in order to measure the large head difference.

Early versions of the hydraulic potentiomanometer used 

a vacuum bottle for collection of the water because hand-held 

pumps did not work well if they became wet (fig. 6). However, 

hand-cranked or motorized peristaltic pumps work well for 

pulling water through the manometer system. A cordless 

drill attached to a peristaltic pump head also can be used as a 

portable pump (J. Lundy, Minnesota Department of Health, 

oral commun., 2005). For a small-volume well and manometer 

system, a large syringe can serve as a pump (D.R. LeBlanc, 

U.S. Geological Survey, oral commun., 2005).

Water samples can be collected with the hydraulic 

potentiomanometer. Many investigators choose to bypass the 

manometer when collecting samples to minimize the potential 

for sample contamination from the tubing.

Sources of Error

Several sources of error attend the use of a hydraulic 

potentiomanometer:

1. Measurement error,

2. Improper leveling of the manometer,

3. Unstable hydraulic head,

4. Improper seal between outer pipe and the sediments,

5. Large bubbles entrained in tubing,

6. Leaks or clogging, and

7. Waves, standing waves, and seiches.

Each item listed above is discussed in detail below.

Measurement Error

Errors in measurement can result from improperly reading the menisci on the manometer. For very small differences 

in head, a common occurrence in highly permeable sediments, 

this error can result in a misinterpretation of the direction of 

flow of water across the sediment-water interface. Capillarity typically is not an issue unless very small diameter plastic 

tubing is used or the tubing diameters on the manometer are 

different. Hydrophobicity, however, may become significant if 

small-diameter plastic tubing is used, in which case the water 

menisci in the tubing may resist movement in response to 

small changes in hydraulic-head gradient.

 Head differences can be amplified by use of a light oil 

in place of air at the top of the manometer (Kelly and Murdoch, 

2003). The degree of amplification depends on the density of 

the light oil relative to the density of water:

dh dhoil

w oil

w

 ¥ 


§

¦

 ́

¶

μ

R R

R , (4)

where

dh is difference in hydraulic head over the 

distance between the sediment-water 

interface and the piezometer screen (L),

dhoil is difference in elevation between the 

oil-water interface on the piezometer side of 

the manometer and oil-water interface on the 

surface-water side of the manometer (L),

ρw is density of water (M V–1),

and

ρoil is density of oil (M V–1).

Kelly and Murdoch (2003) used vegetable oil with a 

density of 0.9 gram per cubic centimeter, which increased the 

head difference tenfold.

Another source of measurement error is the determination of the depth to which the screened interval of the probe is 

inserted. An easy solution for determining this depth is to use 

an engraving tool to mark the outer pipe with depth increments. This distance should be recorded before the outer pipe 

is retracted to expose the screen. Distance typically is relative 

to the center of the screened interval of the probe.

Improper Leveling of the Manometer

This common problem becomes important when the 

two sides of the manometer are separated by a considerable 

distance (as is the case with the manometer shown in fig. 5), or 

when the difference in head is small. Out-of-level error can be 

minimized by installing a bubble level on the manometer and 

by constructing the manometer so the two parallel tubes are 

positioned close to each other (fig. 7).

Unstable Hydraulic Head

Most measurements of difference in head stabilize in a 

matter of seconds to minutes. In low-permeability sediments, 

it can take from tens of minutes to hours for head at the probe 

screen to stabilize. In such cases, observations of difference in 

head are repeated until the difference in head stops changing, 

indicating stabilization. Stabilization time also can provide a 

relative indication of the permeability of the sediments at the 

location of the probe screen.

Improper Seal Between Outer Pipe

and the Sediments

If the hydraulic potentiomanometer is inserted in rocky 

or gravelly sediments, or if the probe is not inserted cleanly 

into the sediments (that is, if the probe is rocked back and 

forth during insertion), or if the probe is inserted a very short 

distance into the sediments, water can flow vertically along the 
52 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

outer surface of the probe, with the result that the difference 

in head between the screen and the surface water is less than 

the actual difference. This “short circuiting” of head can be 

prevented by driving the probe straight into the sediments, or 

by driving the probe farther into the sediments.

Large Bubbles Entrained in Tubing

At many sites, biogenic gas is pulled through the probe 

and is visible in the tubing connecting the probe to the 

manometer. Gas bubbles inside the tubing can change volume 

with a change in temperature and thereby corrupt the difference in head displayed by the manometer. Care should be 

taken to ensure that large bubbles (large enough to extend 

across the entire cross section of the tubing) are removed prior 

to bleeding air back into the top of the manometer to take a 

reading. Very small bubbles also may appear when a strong 

vacuum is applied to pull water through the well screen. These 

bubbles are the result of the water degassing in response to 

the suction pressure. Typically, they do not present a problem 

because they occupy a very small volume, but over time they 

may grow as the water warms. The problem can become significant with increased equilibration time.

Occasionally, small lenses or zones of sediments beneath 

surface-water bodies are unsaturated, commonly because of 

discrete pockets of gas generated from organic decomposition. 

Larger scale areas of unsaturated sediments also have been 

identified, in which case the tubing from the probe is filled 

primarily with air and very little water. Although it is not possible to measure a hydraulic-head difference in these instances, 

the hydraulic potentiomanometer remains useful in that it can 

identify these sometimes unexpected hydrologic conditions. 

Rosenberry (2000) reported a large, apparently permanent 

wedge of unsaturated sediments beneath the edge of a lake 

that was identified on the basis of measurements made with 

the hydraulic potentiomanometer. This unsaturated sediment 

was in direct connection with the adjacent unsaturated zone 

onshore and extended up to 20 meters beyond the shoreline 

of the lake. The hydraulic potentiomanometer also was used 

at a small pond to determine the vertical and areal extent of 

pockets of gas beneath the pond that were several meters in 

diameter. The gas likely was trapped when the pond stage rose 

and the shoreline rapidly moved laterally to cover formerly 

unsaturated near-shore sediments (Rosenberry, 2000).

Leaks or Clogging

Leaks can form (1) at the O-rings that separate the inner 

and outer pipes, (2) between the inner rod and the tubing to 

which it is connected, and (3) between the tubing and the 

manometer. Leaks also can occur within the manometer 

plumbing. Leaks can cause formation of bubbles in the water 

contained within the probe and tubing, which can cause the 

manometer to indicate an erroneous difference in head. O-ring 

leaks can be prevented by liberal use of O-ring grease. Other 

leaks can be eliminated by using clamps, sealant or tape. 

The entire system can be clogged if the well screen is torn or 

absent and sediments are pulled through the tubing. Clogging 

also is likely if the end of the surface-water tubing settles into 

the bed sediments. A screen can be placed over the end of the 

surface-water tube to prevent sediments from entering the tubing. Also, a weight often is applied to the surface-water tube to 

keep the tube from floating to the surface and allowing air to 

be pulled through the tubing.

Waves, Standing Waves, and Seiches

Difference in head between the surface-water body and 

the screened interval of the hydraulic potentiomanometer can 

vary with short-term changes in surface-water stage caused by 

waves, seiches, or even standing waves in fast-moving streams 

or rivers. Waves make it difficult to make a measurement if 

the head difference is small. The surface-water tube can be 

placed inside a small stilling well (even something as simple 

as a coffee can) with holes drilled in the side to dampen stage 

Figure 7. Hydraulic potentiomanometer designed to place 

the manometer tubes connected to the drive probe and to the 

surface-water body close together to minimize out-of-level errors. 

(Photograph by Jim Lundy, Minnesota Department of Health.)

Water

level

Water

level
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 53

fluctuations from waves. Seiches (internal waves) are common 

on large lakes and rivers and can be dealt with by making measurements at the same location multiple times over a period 

that is appropriate for the periodicity of the seiche.

Other Similar Devices

Numerous other devices have been constructed to 

measure difference in head between surface-water bodies and 

the underlying ground water, involving a modification of the 

probe, the method for measuring head difference, or both. 

Squillace and others (1993) modified the hydraulic potentiomanometer by making the probe longer and adding a drive 

hammer in order to place the screened interval at depths as 

great as 3 meters below the sediment-water interface. This 

device was used by Rosenberry (2000) to determine the horizontal and vertical extent of unsaturated sediments beneath a 

lake (fig. 8). Another drive-hammer device has the manometer 

connected to the drive probe to minimize components that 

need to be carried in the field (fig. 9). Mitchell and others 

(1988) clamped the well and lake tubing to a metric ruler to 

create a simple manometer for making measurements of difference in head.

Members of the Cullen Lakes Association in northern 

Minnesota modified a well probe to eliminate the manometer. They used a “mini dipper” small-diameter electric tape 

to make measurements of depth to water inside and outside 

the probe. The measurement outside of the probe was made 

through a length of semirigid tubing; the top of the tubing was 

flush with the top of the probe, and the bottom extended to the 

surface water (fig. 10) (Ted P. Soteroplos and William (Bill) J. 

Maucker, Cullen Lakes Association, written commun., 1995). 

A commercially available, retractable, stainless-steel soil-gas 

vapor probe was used to avoid having to manufacture a retractable well screen.

Several other small-diameter devices also have been 

developed to measure vertical-head gradients beneath surfacewater features. Lee and Cherry (1978) describe the use of a 

flexible plastic tube with a screen attached to the end. The 

tube is driven to depth inside a larger diameter rigid steel pipe 

that is removed once the insertion depth is reached, allowing 

the sediment to collapse around and seal the tube in place in 

the sediment. With the tubing extended above the surface, the 

water level inside the tube is compared to the surface-water 

stage. More recently, a root-watering device, commonly available at hardware stores, has been used to measure vertical 

hydraulic-head gradients beneath surface-water bodies (Wanty 

and Winter, 2000). A coil of tubing is connected to the top of 

the probe, and when positioned properly with respect to the 

water surface, is used to indicate difference in head between 

that in the probe and that of the surface-water body (fig. 11). A 

commercially available probe (MHE PP27) is used to collect 

water samples and to make measurements of difference in 

head beneath the sediment-water interface in much the same 

method (Henry, 2000). This device also makes use of clear 

tubing placed at the water surface to measure difference in 

head (fig. 12).

Several investigators have developed methods for 

determining head gradients at multiple depths beneath the 

sediment-water interface. Duff and others (1998) designed 

a device for collecting water samples from multiple depths 

beneath a streambed. If clear tubing is used, hydraulic heads 

also can be related to stream stage. Lundy and Ferrey (2004) 

used a combination of drive points and multilevel samplers 

that could be left in place for the duration of the study. Their 

study design allowed repeat measurement of head gradients 

and collection of water samples so the investigators could 

determine the extent and growth of a contaminant plume 

that intersected a stream. Both devices allowed rapid measurements and convenient collection of water samples from 

multiple depths.

Figure 8. Hydraulic potentiomanometer probe with drive hammer 

shown driven about 2 meters beneath the lakebed. Manometer 

and hand-crank peristaltic pump are visible in background. 

(Photograph by Donald Rosenberry, U.S. Geological Survey.)
54 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Calm surface-water conditions are required for all of 

these designs that make use of a length of clear tubing inserted 

into the surface-water body. A manometer could be used 

with any of these devices, although most of these alternative 

approaches were developed to avoid use of a manometer in 

order to simplify the measurement system.

Cautions and Suggestions Related to 

Use of the Hydraulic Potentiomanometer

Buried debris, such as logs, rocks, and even old tires, often 

is encountered when driving the hydraulic potentiomanometer 

probe. In most instances, it is possible to reinsert the probe 

0.5 meter away and drive the probe to the desired depth.

The observer should not stand within 1 meter of the probe 

when making a measurement. The weight of the observer can 

compact sediments and cause a several-centimeter change 

in the measured head difference. This artifact is especially 

notable in soft sediments.

If a considerable amount of trapped gas is encountered, 

thus making it difficult to get a bubble-free measurement, it is 

sometimes possible to pull water rapidly through the screen, 

evacuating much of the gas from the sediments near the probe 

screen. After waiting a few minutes, water then can be pulled 

slowly through the screen without pulling additional gas 

bubbles into the tubing.

The screened interval commonly will break when using 

a drive hammer to position a hydraulic potentiomanometer 

probe, especially if many blows are required and the probe is 

made from stainless steel. Stainless steel is relatively brittle, 

and the many holes drilled in the screened interval weaken 

the metal tube, which may lead to failure from the shock of 

the drive hammer. It is advisable to build the device with 

the screen as a separate part that is threaded onto the interior rod of the probe, so damaged or broken screens can be 

removed and replaced. It also is advisable to tighten the screen 

frequently because the shock of driving the probe often loosens the threads connecting the screen to the rest of the probe.

The screen should be retracted inside the outer sheath 

before removing the probe after a measurement has been completed. This prevents the screen from being damaged during 

removal of the probe and also traps the sediment that surrounds the screen while making the measurement. This allows 

a qualitative description of the sediments at the depth at which 

the measurement is made.

Seepage Meters

The seepage meter is one of the most commonly used 

devices for making a direct measurement of the flux of water 

across the sediment-water interface. Early versions were 

developed to measure water losses from irrigation canals 

(Israelson and Reeve, 1944; Warnick, 1951; Robinson and 

Rohwer, 1952; Rasmussen and Lauritzen, 1953). Many of 

these devices were expensive and unwieldy and were little 

used beyond the application to canals. Carr and Winter (1980) 

provide an annotated bibliography of the early literature on 

seepage meters, including drawings of some of the devices. 

Lee (1977) developed an inexpensive and simple meter that 

has changed little during the decades since its inception. Lee’s 

meter consists of the cut-off end of a 208-liter (55-gallon) storage drum, to which is attached a plastic bag that is partially 

filled with a known volume of water (fig. 13). The drum, or 

chamber, is submerged in the surface-water body and placed 

Figure 9. Hydraulic potentiomanometer (created by Joe Magner, 

Minnesota Pollution Control Agency) with manometer connected 

to drive probe. Note the proximity of the lake and drive-point tubes 

to minimize out-of-level errors. Note also the in-line water bottle 

to keep the vacuum pump dry. (Photograph by Donald Rosenberry, 

U.S. Geological Survey.)

Hand

pump

Sample

bottle

Tube to 

surface 

water

Manometer

Drive 

hammer

Drive

probe

Valve
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 55

in the sediment to contain the seepage that crosses that part 

of the sediment-water interface. The bag then is attached to 

the chamber for a measured amount of time, after which the 

bag is removed and the volume of water contained in the bag 

is remeasured. The change in volume during the time the bag 

was attached to the chamber is the volumetric rate of flow 

through the part of the bed covered by the chamber (volume/

time). The volumetric rate of flow then can be divided by the 

approximately 0.25-square-meter area covered by the chamber to express seepage as a flux velocity (distance/time). Flux 

velocity is useful because it normalizes the area covered by 

the seepage meter and allows comparisons of results with 

other studies (and other sizes of seepage meters). Seepage flux 

velocity typically is multiplied by a coefficient that compensates for inefficiencies in flow within the meter, restrictions to flow through the connector between the bag and the 

chamber, and any resistance to movement of the bag as it fills 

or empties.

The range of seepage rates that have been reported from 

coastal and fresh-water settings is approximately five orders 

of magnitude. Values as small as 0.01 centimeter per day have 

been reported (for example, Cherkauer and McBride, 1988; 

Yelverton and Hackney, 1986), although some studies indicate 

that values less than 0.01 centimeter per day (Lee and Cherry, 

1978), 0.04 centimeter per day (Harvey and others, 2004), or 

0.08 centimeter per day (Cable and others, 1997a) are too small 

to be measured accurately. A recently developed meter designed 

for use in benthic ocean settings is capable of measuring exceptionally slow seepage rates as small as 3×10–5 centimeters per 

day (Tryon and others, 2001). Several values of 100 centimeters per day or greater have been reported (100 centimeters per 

day—Asbury, 1990; 130 centimeters per day—Belanger and 

Walker, 1990; 240 centimeters per day—Rosenberry, 2000; 

275 centimeters per day—Paulsen and others, 2001). Duff and 

others (1999) measured a flux of nearly 5,200 centimeters per 

day from a 2- to 3-centimeter-diameter, boiling-sand spring in a 

small stream in northern Minnesota.

The half-barrel seepage meter is relatively easy to use 

and conceptually simple to operate. The cylindrical seepage 

chamber (with bag detached) first is placed on the submerged 

sediment and slowly inserted into the bed with a twisting, 

sediment-cutting action. Care must be taken to ensure a good 

seal between the chamber and the sediment. Buried rocks 

Figure 10. Portable well probe consisting of a commercially 

available retractable soil-gas vapor probe connected to threaded 

pipe with tubing inside the pipe connected to the vapor probe. 

A separate tube taped to the outside of the pipe extends to 

the lake-water surface. (Photograph by Donald Rosenberry, 

U.S. Geological Survey.)

Potentiometric head

of ground water

Potentiometric head

of surface water

Sediment surface

Screened interval, 

approximately 

3 centimeters

Screened interval, 

approximately 

3 centimeters

Figure 11. Well probe constructed from a commercially 

available root feeder with the coiled tubing substituting for a 

manometer. (Modified from Wanty and Winter, 2000.)
56 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

or woody debris can prevent the edges of the chamber from 

extending into the sediment and may allow short-circuiting of 

water beneath the edge of the chamber. Some investigators have 

packed sediments around the outside of the chamber to create 

a good seal (Cable and others, 1997a). Occasionally, in sandy 

or gravelly settings, it is necessary to stand on the chamber 

and gently rock it back and forth to force it into the sediment. 

Sometimes this action is necessary in weedy settings where the 

meter needs to cut through a part of the weed bed in order to 

achieve a good seal. Harvey and others (2000) made circular 

vertical slits in the fibrous peat in order to install seepage meters 

in wetlands in the Florida Everglades. Standing on the chamber 

should be a last resort, however, because rapid emplacement 

can cause “blowouts” of the sediment adjacent to the chamber 

(Lee, 1977), or compress sediments beneath the chamber, and 

disturb the natural rate of water flow through the sediments. 

The chamber should be emplaced with a slight tilt so that the 

opening to which the bag is attached is near the uppermost 

edge of the meter, which facilitates the release of gas from the 

sediment. Sediments often are compressed beneath the seepagemeter chamber during meter insertion, and flow is temporarily 

disrupted. The sediments and flow need to equilibrate before a 

bag is attached. Substantial error can result if measurements are 

made too soon following meter installation.

Lee (1977) originally used the cut-off end of a 208-liter 

(55-gallon) drum, but many other types and sizes of chambers also have been used, including coffee cans (Asbury, 

1990), inverted plastic trash cans (S.E. Hagerthey and 

D.O. Rosenberry, U.S. Geological Survey, written commun., 

1998), lids from desiccation chambers (Duff and others, 

1999), fiberglass domes cemented to a limestone bed (Shinn 

and others, 2002), and even galvanized stock tanks (Landon 

and others, 2001; Rosenberry and Morin, 2004). The size of 

the chamber should be selected for convenience and for the 

expected rate of seepage across the sediment-water interface. A large-diameter meter can measure more accurately 

an extremely small flow across the sediment-water interface, 

and it also better integrates small-scale spatial variability 

in seepage flux. A large meter, however, can be unwieldy 

and it also is more difficult to ensure a good seal in uneven, 

rocky, or debris-laden settings. Alternately, flow from several 

normal-sized chambers can be routed to one seepage bag to 

increase the surface area and integrate spatial heterogeneity 

(Rosenberry, 2005). Large-diameter seepage meters often are 

difficult to remove from the sediments following their use, as 

are smaller-sized chambers inserted into silty or clayey sediment. A simple solution is to insert a length of tubing inside of 

the chamber and blow air into the chamber until the buoyancy 

force lifts the chamber out of the sediments. Some users have 

installed additional openings in the top of the chamber that 

are opened prior to removal of the chamber in order for water 

to flow into the chamber as it is pulled from the sediments. 

Additional openings also reduce the chance for “blowouts” 

or sediment compression during chamber installation.

Much has been written regarding the type and size of 

the bag attached to the chamber (for example, Erickson, 

1981; Shaw and Prepas, 1989; Cable and others, 1997a; 

Isiorho and Meyer, 1999). Bags as small as condoms (Fellows 

and Brezonik, 1980; Duff and others, 1999; Isiorho and Meyer, 

1999; Schincariol and McNeil, 2002) to as large as 15-liter 

trash bags (Erickson, 1981) have been used, with 4-liter 

sandwich bags among the most common choices. Most plastic bags have a “memory effect” caused by the manufacturing 

process that results in a slight pressure created by the bag as 

it moves to a more relaxed position. This can result in errors 

in measurement that become substantial in low-flux settings. 

Shaw and Prepas (1989) reported an anomalous influx of 

water during the first 30 minutes following bag installation 

that they were able to eliminate by prefilling the bags with 

1,000 milliliters of water. Cable and others (1997a) reported 

similar results. Shaw and Prepas (1989) suggested using a 

4-liter-sized bag and adding a known volume of water (1 liter 

or more), even in settings where flow of water was from ground 

water to surface water, because these procedures tended to 

minimize the memory effect. Shaw and Prepas also suggested 

prewetting the bags prior to installation on the chamber to 

Figure 12. MHE PP27 probe used to indicate difference in head 

(modified from Henry, 2000). (Photograph by Mark Henry, Michigan 

Department of Environmental Quality.)

PP27 used as a piezometer/manometer 

to determine the elevation of ground 

water relative to surface water

Sediment surface

Surface water

Sampler 

handle

Water surface

Water level if positive

hydrostatic head

Water level if negative

hydrostatic head

Sediment

Pore fluids enter 

here or are 

injected here

Pore fluids enter 

here or are 
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 57

avoid bias related to the loss of water from adhesion of water 

to the inside of the bag. Blanchfield and Ridgway (1996) 

indicated that seepage rates were inflated by as much as one 

order of magnitude if unfilled bags were used instead of bags 

prefilled with 1,000 milliliters of water. Asbury (1990), reporting results from seepage measurements made where water was 

rapidly flowing from a lake to ground water, indicated that the 

sides of the bag came into contact when the volume of water 

was 500 milliliters or less, which caused a reduction of flow 

out of the bag. Murdoch and Kelly (2003) indicated that the 

hydraulic head necessary to fill a 3,500-milliliter seepage bag 

was smallest when the bag was initially empty, increased to a 

relatively constant value once the bag contained about 100 to 

200 milliliters of water, and then increased rapidly when the 

bag was within 500 to 800 milliliters of being full. They also 

determined that the resistance to filling the bag depended on 

the bag thickness.

Several studies have reported a preference for thin-walled 

plastic bags to minimize resistance to flow to or from the 

bag. Others have reported problems with fish chewing holes 

in the bags and switched to thicker walled bags (Erickson, 

1981). One solution to the fish problem is to place one bag 

inside another. If this is done, however, it is important to 

place small holes in the corners of the outside bag to allow 

water between the bags to drain prior to measurement and to 

allow air to escape from between the bags prior to bag insertion. Another solution is to place the bag in a shelter, which 

also serves the purpose of minimizing the effects of waves 

and currents, described later. Thick-walled bags also have 

been used; intravenous-drip bags or urine-collection bags are 

especially convenient because the tubing that extends from the 

bag already is attached. Recent studies, however, which are 

discussed in the following section on sources of error, indicate 

that bag resistance induces substantial error to seepage measurements, so the use of thick-walled bags should be avoided.

Figure 13. A, Half-barrel seepage meter (modified from Lee and 

Cherry, 1978, used by permission of the Journal of Geoscience 

Education). The top panel shows typical installation with bag 

connected to a tube inserted through a rubber stopper. The 

bottom panel shows installation in shallow water with vent tube 

to allow trapped gas to escape. B, Standard half-barrel seepage 

meter in place in the field. (Photograph by Donald Rosenberry, 

U.S. Geological Survey.) C, Electromagnetic seepage meter 

(foreground) installed next to a half-barrel seepage meter. Cable 

extending from seepage cylinder connects to signal conditioner 

and power supply located on nearby anchored raft. (Photograph 

by Donald Rosenberry, U.S. Geological Survey.)

C

A B

Water surface

Seepage cylinder

Bag

Water

Sediment

Bag

Water

Sediment

Water surface
58 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

In addition, cautions have been issued regarding collecting water-quality samples from a seepage meter (Brock and 

others, 1982; Belanger and Mikutel, 1985). Because the residence time of water contained inside the seepage chamber or 

bag may allow the chemistry of the water to change, samples 

may not be representative of the chemistry of water discharging across the sediment-water interface.

Seepage meters have been modified for use in extreme 

environments. Cherkauer and McBride (1988) created a seepage meter that included a concrete collar for measurement of 

seepage in Lake Michigan, where energy from large waves 

would dislodge unmodified devices (fig. 14). Dorrance (1989) 

and Boyle (1994) each designed seepage meters for use in 

deep water. Both designs consisted of a seepage chamber connected via tubing to a seepage bag installed inside a separate 

housing. Dorrance allowed the bag shelter to float on the 

surface, whereas Boyle suspended the bag housing a short distance beneath the surface. Both designs allowed servicing of 

the bag without the aid of a diver (fig. 15). Hedblom and others (2003) modified a meter to measure gas flux and water flux 

from shallow, contaminated sediments. The device contained a 

mylar bag for collecting gas released from the sediments, and 

it also contained long rods that were driven into the sediment 

to hold the seepage chamber and prevent it from gradually 

sinking into the soft sediments. Shallow-water seepage meters 

also have been used to measure flows near the shoreline where 

seepage rates often are large (Lee and Cherry, 1978) (fig. 13, 

lower panel). Lee and Cherry simply attached the bag to the 

side of the seepage chamber rather than to the top. A bag also 

could be attached to the side of a seepage cylinder that extends 

Figure 14. Seepage meter modified for use in large lakes (from Cherkauer and McBride, 1988. Reprinted from Ground Water with 

permission from the National Ground Water Association, copyright 1988).

Cut-off

55-gallon drum

Lifting 

cable Electrical 

wire

Outlet 1

(air release

with ball valve)

Outlet 1

A. EXTERIOR OF THE 

 FULL METER

PVC 

housing

Sediment

Collection 

bag

Webbing to

support bag

6-inch PVC 

housing

Fuel 

solenoid

Flexible tubing

from outlet 2

Outlet 2b to

collection bag

(power off)

Flexible tubing

from water

Flow

direction

B. CROSS SECTION OF 

 THE DRUM PORTION

Outlet 2

(water 

release)

Outlet 2a to

open water

(power on)

Electical wire

C. LAYOUT OF THE SEEPAGE 

 COLLECTION SYSTEM

22 inches

Concrete

Water

D. FLOW PATTERN 

 THROUGH THE 

 SOLENOID

16

inches

8

inches

4 inches
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 59

above the water surface and contains a free water surface. 

Water then would flow into or out of the bag in order to maintain the same water level inside and outside of the seepage 

chamber. This procedure could allow measurement of seepage 

in the very shallow water closest to the shoreline where seepage rates often are the largest. Waves, however, could create 

potentially large flows through the submerged opening in the 

side of the chamber, leading to large measurement errors. 

Rosenberry and Morin (2004) reported instantaneous flow 

rates into and out of a near-shore seepage cylinder of more 

than 300 milliliters per second.

Seepage meters also have been modified for use in flowing water. In many streams and rivers, currents are sufficient to 

cause the bag to be deflected in a downstream direction, which 

may fold the bag across its connection to the chamber and 

either reduce or pinch off flow to or from the bag. Currents 

also may generate a pressure gradient across the bag membrane that could lead to erroneous measurements (described 

more completely in the next section on sources of error). Bags 

have been installed inside shelters to protect the bag from 

these currents. Designs have included shelters mounted to 

the top of the seepage cylinder (for example, Schneider and 

others, 2005) or shelters that rest on the sediment bed and are 

attached to the seepage cylinder via a short length of tubing 

or hose (for example, Landon and others, 2001). Bag shelters 

also protect the bag from wave action that may cause erroneously large seepage rates (Sebestyen and Schneider, 2001), 

and they maintain the bag in the proper orientation so it cannot 

swing with the current, which could pinch off the opening 

at the bag-connection point. David Lee (Atomic Energy of 

Figure 15. Ground-water seepage meter modified for use in deep water. (Modified from Boyle, 1994. Copyright 1994 by 

the American Society of Limnology and Oceanography, Inc., used with permission.)

Waterproof sealing

compound (RTV)

Cross section of sample bag

Float

Float

clip

Sampling

station

depth line

Hinge

clamp

Aluminum

“sonar” pie plate

White epoxy paint

background on bag

Dyed water

Post

screws

Two-way

valve

Female

reducer

Pail float

Retainer ring

10-liter

pail

Hinged lid

5-liter plastic bag

Initial waterlevel mark

Plastic tube

insert

Depth sonar

Aluminum foil

Smooth 77-liter plastic pail

Surface area

=0.164 square meter

Air vent

10-centimeter corrugated 

plastic tubing

Weighted collar

–2.0 meters

Not to scale

62 centimeters

Ground-water flow
60 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Canada Limited, oral commun., 2006) suggested drilling small 

holes in the part of the tubing that extends inside of the bag to 

further prevent errors should the bag move to pinch off the end 

of the tube.

If a seepage meter is used in combination with the 

hydraulic potentiomanometer, local-scale values for vertical 

hydraulic conductivity can be obtained. A modification of 

particular interest is the “piezoseep” by Kelly and Murdoch 

(2003) that combines a seepage-meter chamber with a piezometer inserted through the center of the chamber. The authors 

replaced the seepage bag with a pump that pulls water at 

known rates from the area covered by the chamber. By accurately measuring the head difference between the piezometer 

point and the surface water in response to various pumping 

rates, they were able to calculate in-situ hydraulic conductivity. The relation between head gradient and seepage flux was 

determined for each meter, which allowed seepage rates to be 

monitored by simply measuring head differences at a desired 

time interval (Murdoch and Kelly, 2003).

Although numerous sources of error exist, especially 

associated with the seepage bag, the seepage meter 

is an attractive choice for quantifying flow across the 

sediment-water interface because of its simplicity and low 

cost. Perhaps as a result, care and training in the use and 

operation of seepage meters commensurate with their cost 

may have led to collection of poor-quality data for some studies. With proper understanding of the operating principles, 

knowledge of sources of error, and care in measurement, accurate determinations of flux across the sediment-water interface 

are possible, as has been demonstrated in many of the papers 

cited herein.

Sources of Error

Sources of error when using seepage meters include:

1. Incomplete seal between seepage-meter chamber and 

sediments, unstable cylinders;

2. Insufficient time between meter installation and first 

measurement;

3. Improper bag-attachment procedures, bag resistance, 

and moving water;

4. Leaks;

5. Measurement error;

6. Flexible seepage-meter chamber;

7. Insufficient or excessive bag-attachment time;

8. Accumulation of trapped gas;

9. Incorrect coefficient to relate measured flux to actual 

flux across the sediment-water interface; and

10. Insufficient characterization of spatial heterogeneity in 

seepage through sediments.

Each item listed above is discussed in detail below.

Incomplete Seal, Unstable Cylinder

Care should be taken to ensure that an effective seal 

exists between the seepage chamber and the sediments. After 

pushing the chamber into the sediments, one can feel around 

the base of the chamber to ensure that the bottom edge of the 

chamber cannot be felt. If the bed is rocky and a good seal is 

impossible, it may be possible to place a mud or bentonite seal 

against the edge of the meter to create a temporary seal. This 

practice, however, may introduce additional errors because 

the seepage immediately beyond the edge of the meter will 

be altered.

Meters installed in soft sediments also may be subject 

to a sealing problem of a different type. If sediments are not 

sufficiently competent to support the weight of the meter, the 

seepage chamber may slowly sink into the sediment following 

emplacement. This will displace water from inside the chamber that will flow into a seepage bag connected to the chamber. 

A solution to this problem is to use taller seepage chambers 

set deeper into the sediments (Fellows and Brezonik, 1980). If, 

for example, a 208-liter storage drum is used, it can be cut in 

half to make a seepage chamber with sidewalls that are about 

45 centimeters tall. Another solution is to anchor the meter 

to rods driven deep into the sediments (Hedblom and others, 

2003). Menheer (2004) designed a chamber with fins that rest 

on the bed surface so that the chamber is installed at a consistent depth in the sediments for every placement.

Insufficient Equilibration Time

This may be the most common source of error for 

scientists inexperienced in the use of seepage meters. It is 

tempting to install the seepage chamber and immediately begin 

making measurements. Sediments first need to be allowed to 

equilibrate following their compression during insertion of 

the seepage chamber. Time between chamber installation and 

first measurement typically is 1 day or more, but a few studies 

have reported waiting shorter times when working in sandy or 

gravelly sediments (table 2). Some investigations indicate that 

an equilibration time as little as 10 to 15 minutes is adequate 

(Lock and John, 1978; Lewis, 1987; Landon and others, 2001). 

Rosenberry and Morin (2004) used an automated seepage meter 

to demonstrate that most of the recovery to predisturbance seepage rates was achieved within 30 minutes after installation of 

the seepage chamber in a sandy lakebed.

Improper Bag-Attachment Procedures, 

Bag Resistance, and Moving Water

The procedure for attaching the bag to the seepage 

chamber depends on the attachment mechanism. With early 

designs, the bag was attached to a small-diameter tube that 

extended through a rubber stopper inserted into the chamber. 

It is important to not apply any pressure to the bag while 

pushing the rubber stopper into the chamber during bag 
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 61

attachment. Significant volumes of water can be forced into or, 

more commonly, out of the bag during attachment. The same 

caution applies to removal of the bag from the chamber. A 

recent improvement in bag-connection design involves using 

a shutoff valve (Cable and others, 1997a) (fig. 16). A bag is 

attached to the shutoff valve and a fitting that connects to the 

threads of the shutoff valve is installed in the seepage chamber. Once the bag is properly filled and emptied of air, the 

valve can be closed for transport until the bag is threaded onto 

the meter, at which time the valve is opened and the measurement period begins. Upon measurement completion, the valve 

is closed and the bag removed for final volume measurement. 

This minimizes the possibility of the investigator inadvertently causing flow into or out of the bag during insertion and 

removal. Other connectors that do not require threads also can 

be used, but the user should test the connector to make sure 

that it does not leak under near-zero pressure conditions.

As mentioned previously, use of thin-walled bags has 

been recommended in numerous seepage studies. Thickwalled bags generate a greater resistance to inflation or deflation, and a larger head gradient is required to effect a change 

in volume inside the bag. Because some bags are constructed 

with a tube already in place (for example, intravenous bags, 

urine-collection bags, solar-shower bags), several studies have 

reported use of these bags in seepage-meter studies. Unless a 

calibration coefficient is determined for measurements made 

with these bags, however, it is likely that the measured seepage rates will substantially underestimate fluxes across the 

sediment-water interface. Murdoch and Kelly (2003) reported 

that thicker bags required a much larger correction multiplier 

(1.88) compared to thin-walled bags (1.25); they also reported 

the measurement variance for thick-walled bags was greater 

than for thin-walled bags. Rosenberry and Menheer (2006) 

reported similar values, ranging from a correction multiplier of 

0.95 for thin-walled bags to 1.89 for a solar-shower bag. Based 

on these observations, use of thick-walled bags is not recommended. Use of condoms as seepage-meter bags also is not 

recommended because they present a temporally variable bag 

resistance that is particularly difficult to account for during 

calibration for (Schincariol and McNeil, 2002).

Bags should be free of air bubbles prior to bag attachment. Bubbles exert a buoyant force on the bag, which can 

place a strain on the bag and either cause an artificial gain or 

loss of water in the bag as it deforms in response to the buoyant force, or prevent the bag from readily inflating or deflating 

to accommodate seepage gains or losses. Harvey and others 

(2000) indicated that excessive gas collected in a seepage 

bag led to artificially large fluxes of water into the bag. They 

designed their seepage meters so that the top of the bag rested 

on the water surface, which eliminated buoyant forces. A 

simple way to remove air from inside the bag is to pull the bag 

beneath the surface of the water body (or beneath the water 

surface in a bucket), with the opening of the bag pointing away 

from the water surface. As the bag is pulled beneath the water, 

air escapes through the opening. The bag can be pulled almost 

completely beneath the water surface until the opening of the 

bag is about to be submerged, at which point the opening is 

closed and the inside of the bag is virtually free of air.

Errors also can be introduced when the observer wades 

out to the seepage meter to attach the bag. In soft sediments, 

the weight of the observer standing next to the seepage meter 

may cause displacement of water from the sediments. This can 

be a problem even in sandy sediments. Rosenberry and Morin 

(2004) reported that seepage increased by more than one order 

of magnitude for several seconds when an observer walked 

within 1 meter of a seepage chamber installed in a sandy 

lakebed, but the seepage rate changed only slightly when averaged over a minute-long period. This source of error is most 

substantial for small rates of seepage and can be avoided if the 

observer floats in the water while attaching and detaching the 

bag. Servicing the meter from a small boat or raft (Harvey and 

others, 2000) works well if the meter can be reached from the 

water surface. Using a short piece of hose or tubing to locate 

the bag 1 to 2 meters away from the seepage chamber also 

minimizes this source of error.

Table 2. Duration between emplacement of seepage meter and first installation of seepage-meter bag (equilibration time) from 

selected studies.

Reference Site Equilibration time

Lock and John, 1978 Lake Taupo, New Zealand 5–10 minutes

Landon and others, 2001 Platte River, Nebraska 10–15 minutes

Lewis, 1987 Coral reefs on Barbados 15 minutes

Rosenberry and Morin, 2004 Mirror Lake, New Hampshire 30–60 minutes

Libelo and MacIntyre, 1994 York River, Virginia 1 hour

Rosenberry, 2000 Lake Belle Taine, Minnesota 1–3 hours

Cable and others, 1997a Gulf Coast, Turkey Point, Florida At least 24 hours

Belanger and Kirkner, 1994 Mountain Lake, Florida 1 day

Erickson, 1981 Williams Lake, Minnesota 2 days

Shaw and Prepas, 1989 Narrow Lake, Alberta 2–3 days

Lee, 1977 Lake Sallie, Minnesota Several days

Belanger and Montgomery, 1992 Laboratory tank tests Several days

Shaw and Prepas, 1990a Narrow Lake, Alberta 2–5 days

Boyle, 1994 Alexander Lake, Ontario A few weeks
62 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

If currents are present, seepage-meter measurements 

can be erroneously large or small, depending on the seepage 

direction. This is the result of velocity head associated with 

moving water,

h v

g v 

2

2 , (5)

where

v is velocity of water flowing past the seepage 

bag (L T–1),

and

g is acceleration due to gravity (L T–2).

Velocity head is one component of the total hydraulic 

head in a stream, which is the sum of velocity head, pressure 

head, and elevation head. Velocity head inside a seepage bag 

is zero because water is not moving appreciably inside the 

bag. Because the flexible plastic bag can easily respond to any 

pressure gradients across the bag surface, the pressure inside 

the bag is the same as outside of the bag. Therefore, the total 

hydraulic head inside the bag is equal to the hydraulic head 

outside of the bag minus the velocity-head component. If flow 

is from ground water to surface water, the velocity-head effect 

will induce additional water to flow into the seepage bag. If 

flow is from surface water to ground water, the velocity-head 

effect will reduce the loss of water from the seepage bag. 

Libelo and MacIntyre (1994) indicated that water flowing at 

a velocity of 0.2 meter per second or faster past an uncovered 

bag resulted in larger rates of seepage than for a bag placed 

inside a protective cover, and that the velocity-head effect 

could more than double the measured seepage flux. They 

indicated this type of error also could result from near-shore 

waves or currents. Murdoch and Kelly (2003) quantified the 

velocity-head effect and indicated it becomes substantial when 

the velocity of the moving water is 0.1 meter per second or 

greater. Both studies indicated that the velocity-head effect 

is proportional to the square of the surface-water velocity, 

consistent with equation 5. Landon and others (2001) used 

bag shelters for their seepage measurements in the Platte 

River in Nebraska. Sebestyen and Schnieder (2001) used a 

plastic shield to protect their seepage-meter bags in a lake in 

New York. Asbury (1990) noted that bags exposed to small 

currents could be pulled to the side by the current, folding the 

bag over the opening and closing off the tubing to which the 

bag was attached. This was an especially important problem 

for flow out of the bag and when the bag was nearly empty of 

water. Conversely, Cable and others (1997a) indicated that currents were not a problem for exposed seepage bags attached 

to meters installed in near-shore regions of the Florida Gulf 

coast, as long as windspeed was less than 15 knots.

A seepage chamber installed in moving water also may 

affect actual seepage rates in the vicinity of the meter. Shinn 

and others (2002) reported that measured seepage was always 

from ground water to surface water at their study sites near 

the Florida Keys, even during intervals when piezometer nests 

indicated reversals in the hydraulic-head gradient in response 

to tidal influences. They attributed this phenomenon to the 

effect of the seepage chamber extending into the flow field 

where ocean currents were relatively strong, which would 

cause water to be advected through the sediment beneath 

the seepage chamber and into the seepage bag. Huettel and 

others (1996) indicated that this process also occurs naturally 

where an uneven sediment bed (ripples, dunes) projects into a 

moving-water flow field. On the upstream side of the obstruction to flow (a dune or, in this instance, a seepage chamber), 

water velocity and, therefore, velocity head decreases, pressure head increases, and the pressure gradient drives flow into 

the sediments, beneath the rim of the chamber, and into the 

chamber. The same process occurs at the downstream side of 

the obstruction where an eddy forms to decrease velocity head 

and increase pressure head. Others who have made seepage 

measurements in marine settings indicated that the seepage 

cylinder is little affected by waves and currents (Corbett and 

Cable, 2003). Regardless of the net effect, the local flow field 

Figure 16. Plastic bag attached to a garden-hose shut-off valve. 

Bag is filled with a known volume of water and then purged of air. 

Valve is closed. Bag is threaded onto male threads on seepage 

meter, and valve then is opened to begin seepage measurement. 

(Photograph by Donald Rosenberry, U.S. Geological Survey.)
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 63

is undoubtedly altered by the presence of a seepage chamber 

positioned in a stream or river. Landon and others (2001) and 

Zamora (2006) reported scouring of the bed at several seepage-meter installations in a sand-bed river.

Leaks

A hole in the seepage meter bag is one of the most common types of leaks. This can be prevented by careful handling 

and frequent testing of the bag, and by “double bagging” the 

bag where fish or crustaceans may make holes in the bag. 

As mentioned previously, if bags are “double bagged,” small 

holes should be placed in the corners of the outer bag to allow 

the evacuation of air trapped between the bags. Bag shelters 

also can minimize the potential for bag damage. The attachment between the bag and the device that connects the bag 

to the chamber is another potential location for leaks. The 

attachment method may involve electrical tape, rubber bands, 

or plastic cable ties, and care should be used to ensure a good 

connection to the tubing or other mechanical connector. One 

solution to this potential problem is to use a bag manufactured 

with an integral plastic tube or sleeve. As previously mentioned, however, many of these bags typically are much thicker 

than food-storage bags and likely resist movement in response 

to changing fluid volume inside the bag. One bag that shows 

promise is designed for use as shipping-protection material. 

The bag is designed to be inflated through a plastic neck that 

is manufactured as part of the bag. A tube is inserted through 

the neck and sealed with adhesive or electrical tape. The bag 

material is quite thin (25 micrometers), and tests conducted 

by Murdoch and Kelly (2003) and Rosenberry and Menheer 

(2006) indicate that it presents little resistance to filling.

Leaks also can occur in the seepage chamber because of 

rust, improper welds, or improper sealing where the tubing 

passes through the rubber stopper (if that is the mechanism used) 

or between the rubber stopper and the chamber. If the seepage 

chamber contains a bung, then a loose bung or a weathered or 

cracked bung gasket also can lead to leaks.

Measurement Error

The change in the volume of water in the seepage-meter 

bag commonly is measured by use of a graduated cylinder. 

Sources for error include misreading the meniscus on the 

graduated cylinder, not holding the graduated cylinder level 

when making a reading, not removing all of the water from 

inside the bag, spilling water during filling or emptying of 

the bag, and misrecording time of attachment and time of 

removal. A funnel is useful for eliminating spills during filling 

and emptying the bag. Another method of measuring volume 

change involves weighing the bag with an accurate, portable 

electronic scale before bag attachment and again following bag removal. Additionally, to reduce the uncertainty of 

volume- measurement error, many investigators commonly 

make three or more measurements at each site and average 

the values.

Flexible Seepage-Meter Chamber

Occasionally the flat, circular end of a half-barrel seepage 

meter can flex downward or upward (sometimes with a sudden, 

audible pop) in response to temperature changes or to pressure 

applied to the metal surface. Standing on the center of the meter 

during emplacement, for example, can cause such flexing. If the 

metal later returns to a more relaxed position while the bag is 

attached, an erroneous measurement will result. Allowing time 

for equilibration between installation and first measurement 

minimizes the likelihood of this occurring during subsequent 

measurements. Other types of chambers also may have insufficient rigidity. Plastic trash cans can flex if the walls of the plastic are too thin. Shinn and others (2002) constructed a seepage 

meter with a flexible top with the intent that the meter would 

flex with the passage of waves; associated pressure perturbations exerted on the ocean bed also would be exerted on the part 

of the bed covered by the meter. This was done to reduce water 

artificially advected into the meter; the experiment met with 

little success.

Insufficient or Excessive Bag-Attachment Time

Bags need to be attached to a seepage meter long enough 

for a measurable change in volume in the bag to occur, but not 

so long that the bag is either full or empty. Bag-attachment 

times can range from seconds to weeks, depending on the 

size of the bag, the diameter of the seepage chamber, and the 

rate of seepage. Problems related to insufficient or excessive 

attachment time are obvious when the bag is full or empty 

upon removal of the bag. A bag that is nearly full or nearly 

empty when being removed also may indicate an erroneous 

flux rate. As mentioned earlier, Murdoch and Kelly (2003) 

determined that the head required to move water into a bag 

increases markedly when the bag is within a few hundred milliliters of being full. Such a condition also is likely when the 

bag is losing water and approaches being empty. Conversely, 

the bag may contain nearly the same volume of water following removal as it contained during attachment, indicating that 

the bag-attachment time was too short. The solution to both 

problems is an iterative one. Subsequent measurement periods 

can be adjusted based on previous incorrect attachment times.

Accumulation of Trapped Gas 

Release of gas from sediments is common where organic 

decomposition produces methane, carbon dioxide, hydrogen 

sulfide, or other gases. If gas accumulates within the seepage 

chamber, it can displace water from inside the chamber that 

then is forced into the bag. There are at least two solutions 

to this problem. A vent tube may be installed at the highest 

point of the meter that extends above the water surface to the 

atmosphere (fig. 13A, lower panel). This allows gas released 

from the sediments covered by the chamber to be released to 

the atmosphere instead of accumulating within the chamber. 

Alternatively, gas may be allowed to escape to the bag. Boyle 

(1994) designed a meter that automatically allowed gas to 
64 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

escape from the meter without being transmitted to the bag. 

Hedblom and others (2003) described a system designed to 

collect both gas and water released from contaminated sediments; they analyzed both gas and water to determine the 

rates of release of various chemicals.

Use of Improper Correction Coefficient

Numerous tests have been conducted to compare 

flow through seepage meters with the rate of seepage in a 

controlled-flow test tank (Lee, 1977; Erickson, 1981; Asbury, 

1990; Cherkauer and McBride, 1988; Dorrance, 1989; 

Belanger and Montgomery, 1992; Murdoch and Kelly, 2003; 

Rosenberry, 2005; Rosenberry and Menheer, 2006). Results 

of these tests indicate that seepage meters undermeasure the 

flux of water across the sediment-water interface because 

of frictional flow loss within the meter, restrictions to flow 

through the connector between the bag and the chamber, and 

any resistance to movement of the bag. Coefficients typically 

are applied to the indicated flux to correct for this problem. 

Erickson (1981) determined that the coefficient was different 

depending on the direction of flow. His studies indicated a 

multiplier of 1.43 was required for flow from ground water to 

surface water and a multiplier of 1.74 for flow from surface 

water to ground water. Belanger and Montgomery (1992) indicated a multiplier of 1.30 was required to correct for measurements of flow from ground water to surface water. Cherkauer 

and McBride (1988) used a correction factor of 1.6 for flow 

from ground water to surface water, and Dorrance (1989) 

indicated that a multiplier of 1.61 was required for his seepage 

meter designed for quantifying loss of water from a reservoir. 

Asbury (1990) used a multiplier for flow either into or out of a 

surface-water body of 1.11; he attributed his lower multiplier 

to his using a larger diameter connector (19 millimeters) than 

other investigators. Murdoch and Kelly (2003) determined 

measurement inefficiency by using highly accurate manometers to measure head loss, and reported correction factors of 

1.25 to 1.82, depending on the type of bag used. Rosenberry 

(2005) used large diameter (9.5-millimeter minimum inside 

diameter) connection materials and a thin-walled 4-liter 

bag with a Lee-type seepage chamber to obtain a correction 

factor of 1.05.

Fellows and Brezonik (1980) related seepage-meter 

efficiency to the diameter of the connector between the meter 

and the bag and to seepage velocity. Their results indicated 

that head loss increased with decreasing tubing diameter and 

with increasing seepage velocity (fig. 17); they suggested that a 

tubing diameter larger than 5 millimeters would not cause loss 

of efficiency for most fluxes commonly measured with seepage meters. On the basis of their experiments, however, they 

altered their seepage-meter design to use a 9-millimeter opening 

instead of a 5-millimeter opening between the bag and the 

meter. Rosenberry and Morin (2004) found a similar response 

by positioning a pressure transducer inside a seepage meter 

and recording pressure changes in response to routing seepage through a range of tubing diameters. Pressure changed by 

21 millimeters of water head when seepage was forced to flow 

through 4-millimeter-diameter tubing, but the pressure change 

was only 4 millimeters of water head when flow was routed 

through 7.9-millimeter-diameter tubing. Harvey and others 

(2000) used a large-diameter (19-millimeter) connection system 

to eliminate any concern regarding tubing resistance in a study 

of seepage from wetlands in the Florida Everglades. Rosenberry 

and Menheer (2006) describe a seepage-meter calibration tank 

for determining the efficiency of various seepage-meter designs.

Insufficient Characterization of Spatial 

Heterogeneity in Seepage Through Sediments

Successful extrapolation of point measurements of seepage to whole-lake systems requires that the seepage measurements adequately characterize the larger scale integrated 

exchange between ground water and surface water. This 

extrapolation can be difficult because small-scale spatial 

variability in flux across the sediment-water interface is common. Measurements at several locations may be required to 

adequately characterize seepage on a meaningful spatial scale. 

Shaw and Prepas (1990a) determined that seepage rates could 

vary by more than a factor of 2 when meters were installed 

only 1 meter apart (fig. 18). They found that seepage flux in a 

2-square-meter area was lognormally distributed, and the variance in seepage increased with seepage velocity. They attributed seepage variability to variability in hydraulic conductivity 

of the lakebed. Shaw and Prepas (1990b) recommended 

making seepage measurements at additional transects in a lake 

rather than making replicate measurements at a single transect 

to best characterize spatial variability in lakebed seepage.

0 56 113 169 226 282 339

FLOW, IN MILLILITERS PER MINUTE

RESISTANCE TO FLOW, IN CENTIMETERS OF WATER

One observation

Two observations

SEEPAGE FLUX THROUGH STANDARD HALF-BARREL METER, 

IN CENTIMETERS PER DAY

0

0

2

3

4

5

6

0.1 cm ID

0.21 cm ID

0.3 cm ID

0.5 cm ID

1

100 200 300 400 500 600

395

700

Figure 17. Resistance to flow related to tubing diameter and 

rate of seepage. Seepage flux assumes a 0.25-square-meterarea seepage meter. (Modified from Fellows and Brezonik, 1980; 

copyright 1980 by the American Water Resources Association, 

used with permission.)
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 65

Asbury (1990) addressed the question of seepage-meter 

precision related to lakebed heterogeneity by installing 

25 seepage meters on an 8-meter by 8-meter grid. His results 

(table 3) showed a large decrease in seepage with distance 

from shore and then a reversal in seepage direction farther 

from shore as was expected based on previous results. The 

five measurements made at each distance from shore showed 

remarkable consistency near the shoreline where seepage rates 

were largest, but seepage variability increased with distance 

from shore out to 6 meters from shore. Beyond that distance, 

seepage direction reversed and the variance decreased slightly.

Belanger and Walker (1990) tested small-scale spatial 

variability in seepage by placing two to three seepage meters 

5 meters apart at seven different sites. They found very good 

reproducibility at five of the sites where seepage rates were 

relatively small. At the other two sites, where seepage rates 

were much larger, they attributed the greater spatial variability 

in seepage to the presence of springs in the area.

Michael and others (2003) used 40 seepage meters to 

measure seepage variability in four transects perpendicular from 

shore on a 50-meter spacing in a saltwater bay near Cape Cod, 

Massachusetts. They detected bands of seepage with distance 

from shore that were parallel to the shoreline and determined 

that as long as meters are arranged in transects, errors associated with reducing the number of transects are not unacceptably 

large. Departures from flux estimated with all four transects 

were 9, 4, and 3 percent when data from one, two, or three 

transects were used. They also placed seepage meters in clusters 

with 1-meter spacing and found spatial variability in seepage of 

the same magnitude as with the 50-meter spacing.

Approaches to characterizing seepage variability include 

either making numerous measurements in each area of interest, in a manner similar to the approach of Asbury (1990) or 

Michael and others (2003), or using larger seepage chambers that cover larger areas of the sediment-water interface 

and better integrate the heterogeneity in seepage. Typically, 

the scale of interest is a characterization of seepage for an 

entire surface-water body or shoreline reach. In this instance, 

resources may be better spent characterizing seepage along a 

number of transects positioned throughout the area of interest, 

which characterizes spatial variability on a scale appropriate 

for the interests of the study (for example, Michael and others, 

2003). Rosenberry (2005) addressed the heterogeneity issue by 

routing flow from several seepage chambers to one collection 

bag. With such a system, spatial variability in seepage is averaged in one measurement, which also reduces bag-collection 

time and labor costs. Head loss did not substantially reduce the 

efficiency of the ganged seepage measurement when 3-meter 

lengths of garden hose (14-millimeter diameter) were used to 

connect the seepage chambers.

Best-Measurement Practices for Manual 

Seepage Meters

The following recommendations are presented for 

minimizing errors associated with making seepage-meter 

measurements:

1. Use a rigid seepage chamber. A diameter of approximately 0.5 meter seems to be a useful compromise 

between maximizing areal coverage and maximizing 

convenience of use. Make certain that the entire rim of the 

seepage chamber is seated at least a few centimeters into 

the sediment-water interface. For sandy sediments, 1 hour 

is probably a sufficient time to wait between installation 

and first bag measurements. For softer sediments, it may 

be prudent to wait 1 day to begin measurements.

2. Use several meters to characterize spatial heterogeneity 

at a scale that is appropriate for the interests of the study. 

Seepage chambers can be ganged to integrate seepage 

heterogeneity over a larger area and also to minimize the 

number of required bag measurements.

3. Use a shelter to protect the bag from waves and currents 

and to ensure that the bag orientation is maintained in a 

position that will not close or restrict the opening between 

the bag and the bag-connection system.

4. Use a large-diameter bag-connection system, especially 

when fast seepage rates are expected. A diameter 9 millimeters or larger is suggested.

5. Use thin-walled bags to minimize bag resistance. A bag 

size of 4 liters is convenient for most seepage rates.

6. Prefill the bag with 500 to 1,000 milliliters of water 

prior to bag attachment. If seepage from surface water to 

ground water is expected, a larger initial volume of water 

may be warranted. Do not fill the bag to more than about 

75 percent of its capacity.

7. Seepage-meter correction coefficients have been decreasing over time as seepage-meter designs become more 

efficient. If the suggestions listed above are followed, a 

coefficient from 1 to 1.1 will provide a good estimate of 

true seepage rates for most meter designs.

Figure 18. Seepage flux measured at two seepage meters 

located 1 meter apart. Flux values are in meters per second. 

(Modified from Shaw and Prepas, 1990a; copyright 1990, reprinted 

from Journal of Hydrology, used with permission from Elsevier.)

9

1

2

3

4

5

6

7

10 11

AUGUST 1984

SEEPAGE FLUX, 

IN METERS PER SECOND x 10–8

12 13 14
66 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Automated Seepage Devices

Temporal variability in flux across the interface between 

ground water and surface water has been investigated on a seasonal scale (for example, Schneider and others, 2005; Michael 

and others, 2005), but temporal variability on a weekly or 

shorter time scale has not been extensively investigated. 

Several investigators have made numerous measurements over 

time to measure the temporal variability (Lee, 1977; Cable 

and others, 1997b; Sebestyen and Schneider, 2001), but this 

is a labor-intensive endeavor. Recently developed automated 

devices allow measurement of seepage responses to temporal events such as seiches (Taniguchi and Fukuo, 1996), 

tides (Paulsen and others, 2001, 2004; Taniguchi, 2002), and 

recharge events (Rosenberry and Morin, 2004).

Several of these automated devices use heat-pulse technology to measure flow. One such meter uses sensors originally developed for measuring sap flow in plants (Taniguchi 

and Fukuo, 1993, 1996) and records the data with a digital 

datalogger enclosed in the submerged seepage meter. Another 

design uses the same heat-pulse technology but also includes 

sensors for collection of water-quality data (Krupa and 

others, 1998). This device is tethered to a raft that is anchored 

above the submerged seepage meter. Taniguchi has recently 

improved the heat-pulse method with a continuous heat-source 

seepage meter (Taniguchi and others, 2003).

Paulsen and others (2001) developed an automated 

seepage meter that makes use of acoustic-velocity technology more commonly used to measure surface-water flow. 

Their sensor can measure flux velocity values ranging from 

about 1 to at least 275 centimeters per day over an exchange 

area of 0.21 square meter. Menheer (2004) also used an 

acoustic-velocity sensor to measure seepage in a benthic-flux 

chamber that was designed to quantify flow of mercury from 

ground water to surface water. Another automated seepage 

meter replaces the plastic bag with an electromagnetic flow 

meter typically used to measure flow velocity in boreholes 

(Rosenberry and Morin, 2004). With the flow meter attached 

to a 1.1-meter-diameter chamber, a modified version of 

their sensor can measure flux velocities ranging from 4 to 

4,000 centimeters per day.

A device developed for use in deep-ocean environments 

uses a chemical tracer that is injected into an outlet tube of 

the seepage meter (Tyron and others 2001). A pair of samplecollection coils on either side of the injection point provides a 

record of the tracer based on dilution of the injectate relative 

to the seepage rate. Water in the coils is sampled upon retrieval 

of the meter and analyzed to provide time-series data of the 

seepage rate. This device can measure seepage rates ranging 

from 3×10–5 to 4 centimeters per day.

Dye-dilution seepage meters make use of dye-dilution 

chambers, the size of which can be adjusted to accommodate a 

wide range of seepage rates (Sholkovitz and others, 2003). The 

combination of chambers used with the meter developed by 

Sholkovitz and others can measure seepage rates ranging from 

less than 0.1 to more than 300 centimeters per day. The authors 

point out that smaller chambers could be used to measure 

smaller seepage rates at deep-ocean installations.

The Taniguchi and Krupa automated seepage meters 

have been in use for 10 to 15 years, but as of 2007, the other 

meters are in the early stages of use. These automated devices 

are not subject to the previously mentioned problems associated with the use of seepage bags. Although all of the automated devices are fitted to a seepage chamber and are subject 

to the chamber- and connection-related errors discussed 

above, those errors should be relatively small compared to 

bag-related errors.

Methods Selection

Selection of the appropriate methods of calculation and 

(or) measurement is one of the most important decisions to be 

made when quantifying exchange between ground water and 

surface water. Of the three methods presented in this chapter, 

each has advantages and disadvantages that may or may not 

be relevant to the study area of interest. Although it is not 

possible to anticipate all situations, table 4 provides a general 

guideline to conditions or situations in which each method 

is particularly well- or ill-suited. As indicated in Chapter 1, 

the use of more than one method to quantify the exchange 

between ground water and surface water can be informative 

and valuable to increasing the confidence in the flux values 

estimated or calculated.

Table 3. Seepage flux with distance from shore and distance along shore on an 8-meter by 8-meter grid (2-meter seepage-meter 

spacing) (from Asbury, 1990).

Distance

from shore

(meters)

Seepage flux (centimeters per day)

Distance along shore ( meters) Average Variance 0 2 4 6 8 

2 –11.3 –11.2 –11.4 –12.1 –11.8 –11.56 0.143

4 –8.4 –9.3 –10.4 –10.5 –6.5 –9.02 2.727

6 –3.5 –6.7 –6.4 –0.8 –4.5 –4.38 5.767

8 0.9 2.4 3.8 3.1 4.9 3.02 2.257

10 3.7 0.3 2.3 0.2 1.2 1.54 2.173
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 67

Table 4. Conditions for which methods for quantifying flow between ground water and surface water are well- or ill-suited.

Method Well-suited for: Ill-suited for:

Calculations from water levels in 

network of wells and surfacewater stage

•	 Basin-scale quantification

•	 Distinguishing areas of inflow from areas 

of outflow

•	 Determining large-scale aquifer characteristics

•	 Relatively homogeneous aquifers

•	 Determining flux of some chemicals that enter or leave 

a surface-water body

•	 Steep and (or) rocky shorelines where installation of 

wells is difficult or impossible

•	 Low-lying terrain where shoreline migration is large 

and evapotranspiration is a significant factor

•	 Areas with complex geology or vertical flow regimes 

where effective depth of aquifer is nearly impossible 

to determine

Hydraulic potentiomanometer 

and well-probe measurements

•	 Fine sand to medium gravel sediments

•	 Quick reconnaissance for qualitative determination of direction of flow

•	 Determining variability of vertical hydraulic 

gradient with depth

•	 Collection of water-quality samples

•	 Fine-grained sediments

•	 Rocky shorelines or bedrock

•	 Surface-water body with any appreciable wave action

•	 Fast-flowing water

•	 Organic, gas-rich sediments

Seepage-meter measurements •	 Direct measurement of seepage flux

•	 Areal distribution of seepage flux

•	 Sediments ranging from clayey-silt to finemedium gravel

•	 Calm-water settings

•	 Shallow-water settings

•	 Surface-water body with any appreciable wave action

•	 Areas with strong currents or fast-flowing water

•	 Very soft, low-density sediments

•	 Rocky sediment beds

•	 Bed areas with dense vegetation

References

Asbury, C.E., 1990, The role of groundwater seepage in sediment chemistry and nutrient budgets in Mirror Lake, New 

Hampshire: Cornell University, Ph.D., 275 p.

Belanger, T.V., and Kirkner, R.A., 1994, Ground-water/

surface-water interaction in a Florida augmentation lake: 

Lake and Reservoir Management, v. 8, no. 2, p. 165–174.

Belanger, T.V., and Mikutel, D.F., 1985, On the use of 

seepage meters to estimate groundwater nutrient loading 

to lakes: Water Resources Bulletin, v. 21, no. 2, p. 265–272.

Belanger, T.V., and Montgomery, M.T., 1992, Seepage 

meter errors: Limnology and Oceanography, v. 37, no. 8, 

p. 1787–1795.

Belanger, T.V., and Walker, R.B., 1990, Ground water seepage in the Indian River Lagoon, Florida: American Water 

Resources Association Technical Publication Series TPS, 

v. 90–2, p. 367–375.

Blanchfield, P.J., and Ridgway, M.S., 1996, Use of seepage 

meters to measure groundwater flow at brook trout redds: 

Transactions of the American Fisheries Society, v. 125, 

p. 813–818.

Boyle, D.R., 1994, Design and seepage meter for measuring groundwater fluxes in the nonlittoral zones of 

lakes—Evaluation in a boreal forest lake: Limnology and 

Oceanography, v. 39, no. 3, p. 670–681.

Brock, T.D., Lee, D.R., Janes, D., and Winek, D., 1982, 

Groundwater seepage as a nutrient source to a drainage 

lake; Lake Mendota, Wisconsin: Water Resources, v. 16, 

p. 1255–1263.

Brunke, M., 1999, Colmation and depth filtration within 

streambeds—Retention of particles in hyporheic interstices: International Review of Hydrobiology, v. 84, no. 2, 

p. 99–117.

Buchanan, T.J., and Somers, W.P., 1982, Stage measurement 

at gaging stations: U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 3, chap. A7, 28 p.

Cable, J.E., Burnett, W.C., Chanton, J.P., Corbett, D.R., and 

Cable, P.H., 1997a, Field evaluation of seepage meters in 

the coastal marine environment: Estuarine, Coastal and 

Shelf Science, v. 45, p. 367–375.

Cable, J.E., Burnett, W.C., and Chanton, J.P., 1997b, Magnitude and variations of groundwater seepage along a Florida 

marine shoreline: Biogeochemistry, v. 38, p. 189–205.

Carr, M.R., and Winter, T.C., 1980, An annotated bibliography 

of devices developed for direct measurement of seepage: 

U.S. Geological Survey Open-File Report 80–344, 38 p.

Cedergren, H.R., 1997, Seepage, drainage, and flow nets 

(3d ed.): New York, John Wiley and Sons, 465 p.

Cherkauer, D.A., and McBride, J.M., 1988, A remotely operated seepage meter for use in large lakes and rivers: Ground 

Water, v. 26, no. 2, p. 165–171.
68 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Corbett, D.R., and Cable, J.E., 2003, Seepage meters and 

advective transport in coastal environments—Comments on 

“Seepage Meters and Bernoulli’s Revenge” by E.A. Shinn, 

C.D. Reich, and T.D. Hickey, 2002, Estuaries 25:126–132: 

Estuaries, v. 26, no. 5, p. 1383–1389.

Davis, S.N., and DeWiest, R.J.M., 1991, Hydrogeology, Malabar, Florida: Krieger Publishing, 463 p.

Dorrance, D.W., 1989, Streaming potential and seepage meter 

studies at Upper Lake Mary near Flagstaff, Arizona: Tucson, 

University of Arizona, Masters thesis, 182 p.

Duff, J.H., Murphy, F., Fuller, C.C., Triska, F.J., Harvey, J.W., 

and Jackman, A.P., 1998, A mini drivepoint sampler for 

measuring pore water solute concentrations in the hyporheic 

zone of sand-bottom streams: Limnology and Oceanography, v. 43, no. 6, p. 1378–1383.

Duff, J.H., Toner, B., Jackman, A.P., Avanzino, R.J., and 

Triska, F.J., 1999, Determination of groundwater discharge 

into a sand and gravel bottom river—A comparison of chloride dilution and seepage meter techniques: Verh. Internat. 

Verein. Limnol., v. 27, p. 406–411.

Erickson, D.R., 1981, A study of littoral groundwater seepage at Williams Lake, Minnesota, using seepage meters 

and wells: Minneapolis, University of Minnesota, Master’s 

thesis, 135 p.

Fellows, C.R., and Brezonik, P.L., 1980, Seepage flow into 

Florida lakes: Water Resources Bulletin, v. 16, no. 4, 

p. 635–641.

Fetter, C.W., 2000, Applied hydrogeology (4th ed.): Englewood Cliffs, N.J., Prentice Hall, 691 p.

Fleckenstein, J.H., Niswonger, R.G., and Fogg, G.E., 2006, 

River-aquifer interactions, geologic heterogeneity, and lowflow management: Ground Water, v. 44, no. 6, p. 837–852.

Harbaugh, A.W., 2005, MODFLOW-2005, the U.S. Geological Survey modular ground-water model—The groundwater flow process: U.S. Geological Survey Techniques and 

Methods 6–A16, 237 p.

Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, 

M.G., 2000, MODFLOW-2000, the U.S. Geological Survey 

modular ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. Geological Survey Open-File Report 2000–92, 121 p.

Harvey, J.W., Krupa, S.L., Gefvert, C.J., Choi, J., Mooney, 

R.H., and Giddings, J.B., 2000, Interaction between ground 

water and surface water in the northern Everglades and 

relation to water budgets and mercury cycling—Study 

methods and appendixes: U.S. Geological Survey Open-File 

Report 2000–168, 395 p.

Harvey, J.W., Krupa, S.L., and Krest, J.M., 2004, Ground 

water recharge and discharge in the Central Everglades: 

Ground Water, v. 42, no. 7, p. 1090–1102.

Hedblom, E., Costello, M., and Huls, H., 2003, Integrated field 

sampling for design of a remedial cap: Cincinnati, Ohio, 

Proceedings of the In-Situ Contaminated Sediment Capping 

Workshop, May 12–14, 2003, p. 19.

Henry, M.A., 2000, Appendix D: MHE push-point sampling 

tools, in Proceedings of the Ground-Water/Surface-Water 

Interactions Workshop, July 2000: U.S. Environmental Protection Agency, EPA/542/R–00/007, p. 199–200.

Hiscock, K.M., and Grischek, T., 2002, Attenuation of groundwater pollution by bank filtration: Journal of Hydrology, 

v. 266, p. 139–144.

Huettel, M., Ziebis, W., and Forster, S., 1996, Flow-induced 

uptake of particulate matter in permeable sediments: 

Limnology and Oceanography, v. 41, no. 2, p. 309–322.

Hunt, R.J., Haitjema, H.M., Krohelski, J.T., and Feinstein, 

D.T., 2003, Simulating ground water—Lake interactions; approaches and insights: Ground Water, v. 41, no. 2, 

p. 227–237.

Hvorslev, M.J., 1951, Time lag and soil permeability in ground 

water observations: U.S. Army Corps of Engineers Waterways Experimental Station Bulletin no. 36, 50 p.

Isiorho, S.A., and Meyer, J.H., 1999, The effects of bag type 

and meter size on seepage meter measurements: Ground 

Water, v. 37, no. 3, p. 411–413.

Israelson, O.W., and Reeve, R.C., 1944, Canal lining experiments in the Delta Area, Utah: Utah Agricultural Experimental Station, Bulletin 313, p. 15–35.

Kelly, S.E., and Murdoch, L.C., 2003, Measuring the hydraulic conductivity of shallow submerged sediments: Ground 

Water, v. 41, no. 4, p. 431–439.

Kim, K., Anderson, M.P., and Bowser, C.J., 1999, Model calibration with multiple targets—A case study: Ground Water, 

v. 37, no. 3, p. 345–351.

Krabbenhoft, D.P., and Anderson, M.P., 1986, Use of a 

numerical ground-water flow model for hypothesis testing: 

Ground Water, v. 24, p. 49–55.

Krupa, S.L., Belanger, T.V., Heck, H.H., Brock, J.T., and 

Jones, B.J., 1998, Krupaseep—The next generation seepage meter, in International Coastal Symposium (ICS 

98), Journal of Coastal Research Special Issue no. 26: 

Fort Lauderdale, Fla., Coastal Education Research Foundation, p. 210–213.
Use of Monitoring Wells, Portable Piezometers, and Seepage Meters to Quantify Flow 69

Landon, M.K., Rus, D.L., and Harvey, F.E., 2001, Comparison of instream methods for measuring hydraulic conductivity in sandy streambeds: Ground Water, v. 39, no. 6, 

p. 870–885.

Leake, Stanley A., 1997, Modeling ground-water flow with 

MODFLOW and related programs: U.S. Geological Survey 

Fact Sheet FS–121–97, 4 p.

Lee, D.R., 1977, A device for measuring seepage flux in lakes 

and estuaries: Limnology and Oceanography, v. 22, no. 1, 

p. 140–147.

Lee, D.R., and Cherry, J.A., 1978, A field exercise on groundwater flow using seepage meters and mini-piezometers: 

Journal of Geological Education, v. 27, p. 6–20.

Lee, T.M., and Swancar, A., 1997, Influence of evaporation, 

ground water, and uncertainty in the hydrologic budget 

of Lake Lucerne, a seepage lake in Polk County, Florida: 

U.S. Geological Survey Water Supply Paper 2439, 61 p.

Lewis, J.B., 1987, Measurements of groundwater seepage flux 

onto a coral reef—Spatial and temporal variations: Limnology and Oceanography, v. 32, no. 5, p. 1165–1169.

Libelo, E.L., and MacIntyre, W.G., 1994, Effects of surfacewater movement on seepage-meter measurements of flow 

through the sediment-water interface: Applied Hydrogeology, v. 2, no. 4, p. 49–54.

Lock, M.A., and John, P.J., 1978, The measurement of 

groundwater discharge into a lake by direct method: Internationale Revue der gesamten Hydrobiologie, v. 63, no. 2, 

p. 271–275.

Lundy, J.R., and Ferrey, Mark, 2004, Direct measurement of 

ground water contaminant discharge to surface water, in

Proceedings of National Water Quality Monitoring Council 

2004 National Monitoring Conference, May 17–20, 2004: 

Chattanooga, Tenn., 10 p.

McCobb, T.D., LeBlanc, D.R., and Socolow, R.S., 1999, A 

siphon gage for monitoring surface-water levels: Journal 

of the American Water Resources Association, v. 35, no. 5, 

p. 1141–1146.

Menheer, M.A., 2004, Development of a benthic-flux chamber for measurement of ground-water seepage and water 

sampling for mercury analysis at the sediment-water 

interface: U.S. Geological Survey Scientific Investigations 

Report 2004–5298, 14 p.

Michael, H.A., Lubetsky, J.S., and Harvey, C.F., 2003, 

Characterizing submarine groundwater discharge—A 

seepage meter study in Waquoit Bay, Massachusetts: 

Geophysical Research Letters, v. 30, no. 6, p. 1297. 

[doi:10.1029/2002GL016000]

Michael, H.A., Mulligan, A.E., and Harvey, C.F., 2005, Seasonal oscillations in water exchange between aquifers and 

the coastal ocean: Nature, v. 436, p. 1145–1148.

Mitchell, D.F., Wagner, K.J., and Asbury, C., 1988, Direct 

measurement of groundwater flow and quality as a lake 

management tool: Lake and Reservoir Management, v. 4, 

no. 1, p. 169–178.

Murdoch, L.C., and Kelly, S.E., 2003, Factors affecting the performance of conventional seepage meters: 

Water Resources Research, v. 39, no. 6, p. SWC 2–1. 

[doi:10.1029/2002WR001347]

Nield, S.P., Townley, L.R., and Barr, A.D., 1994, A framework for quantitative analysis of surface water-groundwater 

interaction—Flow geometry in a vertical section: Water 

Resources Research, v. 30, no. 8, p. 2461–2475.

Paulsen, R.J., Smith, C.F., O’Rourke, D., and Wong, T., 2001, 

Development and evaluation of an ultrasonic ground water 

seepage meter: Ground Water, v. 39, no. 6, p. 904–911.

Paulsen, R.J., O’Rourke, D., Smith, C.F., and Wong, T.-F., 

2004, Tidal load and salt water influences on submarine 

ground water discharge: Ground Water, v. 42, no. 7, 

p. 990–999.

Rasmussen, W., and Lauritzen, C.W., 1953, Measuring seepage from irrigation canals: Agricultural Engineering, v. 34, 

p. 326–330.

Robinson, A.R., and Rohwer, C., 1952, Study of seepage 

losses from irrigation channels: U.S. Department of Agriculture, Soil Conservation Service, Progress Report, 42 p.

Rosenberry, D.O., 2000, Unsaturated-zone wedge beneath a 

large, natural lake: Water Resources Research, v. 36, no. 12, 

p. 3401–3409.

Rosenberry, D.O., 2005, Integrating seepage heterogeneity 

with the use of ganged seepage meters: Limnology and 

Oceanography, Methods, v. 3, p. 131–142.

Rosenberry, D.O., and Menheer, M.A., 2006, A system for 

calibrating seepage meters used to measure flow between 

ground water and surface water: U.S. Geological Survey 

Scientific Investigations Report 2006–5053, 21 p.

Rosenberry, D.O., and Morin, R.G., 2004, Use of an electromagnetic seepage meter to investigate temporal variability 

in lake seepage: Ground Water, v. 42, no. 1, p. 68–77.

Rovey, C.W., II, and Cherkauer, D.S., 1995, Scale dependency 

of hydraulic conductivity measurements: Ground Water, 

v. 33, no. 5, p. 769–780.

Schincariol, R.A., and McNeil, J.D., 2002, Errors with small 

volume elastic seepage meter bags: Ground Water, v. 40, 

no. 6, p. 649–651.
70 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Schneider, R.L., Negley, T.L., and Wafer, C., 2005, Factors 

influencing groundwater seepage in a large, mesotrophic 

lake in New York: Journal of Hydrology, v. 310, p. 1–16.

Schubert, J., 2002, Hydraulic aspects of riverbank filtration—

Field studies: Journal of Hydrology, v. 266, p. 145–161.

Schulze-Makuch, D., Carlson, D.A., Cherkauer, D.S., and 

Malik, P., 1999, Scale dependency of hydraulic conductivity in heterogeneous media: Ground Water, v. 37, no. 6, 

p. 904–919.

Sebestyen, S.D., and Schneider, R.L., 2001, Dynamic temporal patterns of nearshore seepage flux in a headwater 

Adirondack lake: Journal of Hydrology, v. 247, p. 137–150.

Shaw, R.D., and Prepas, E.E., 1989, Anomalous, short-term 

influx of water into seepage meters: Limnology and Oceanography, v. 34, no. 7, p. 1343–1351.

Shaw, R.D., and Prepas, E.E., 1990a, Groundwater-lake interactions, I—Accuracy of seepage meter estimates of lake 

seepage: Journal of Hydrology, v. 119, p. 105–120.

Shaw, R.D., and Prepas, E.E., 1990b, Groundwater-lake interactions, II—Nearshore seepage patterns and the contribution of groundwater to lakes in central Alberta: Journal of 

Hydrology, v. 119, p. 121–136.

Sheets, R.A., Darner, R.A., and Whitteberry, B.L., 2002, Lag 

times of bank filtration at a well field, Cincinnati, Ohio, 

USA: Journal of Hydrology, v. 266, p. 162–174.

Shinn, E.A., Reich, C.D., and Hickey, T.D., 2002, Seepage 

meters and Bernoulli's Revenge: Estuaries, v. 25, no. 1, 

p. 126–132.

Sholkovitz, E., Herbold, C., and Charette, M., 2003, An automated dye-dilution based seepage meter for the time-series 

measurement of submarine groundwater discharge: Limnology and Oceanography—Methods, v. 1, p. 16–28.

Siegel, D.I., and Winter, T.C., 1980, Hydrologic setting of 

Williams Lake, Hubbard County, Minnesota: U.S. Geological Survey Open-File Report 80–403, 56 p.

Squillace, P.J., Liszewski, M.J., and Thurman, E.M., 1993, 

Agricultural chemical interchange between ground 

water and surface water, Cedar River basin, Iowa and 

Minnesota—A study description: U.S. Geological Survey 

Open-File Report 92–0085, 26 p.

Taniguchi, M., 2001, Evaluation of the groundwater capture 

zone for modelling of nutrient discharge: Hydrological 

Processes, v. 15, p. 1939–1949.

Taniguchi, M., 2002, Tidal effects on submarine groundwater 

discharge into the ocean: Geophysical Research Letters, 

v. 29, no. 12, p. 2–1. [doi:10.1029/2002GL014987]

Taniguchi, M., Burnett, W.C., Smith, C.F., Paulsen, R.J., 

O'Rourke, D., Krupa, S.L., and Christoff, J.L., 2003, Spatial 

and temporal distributions of submarine groundwater discharge rates obtained from various types of seepage meters 

at a site in the Northeastern Gulf of Mexico: Biogeochemistry, v. 66, p. 35–53.

Taniguchi, M., and Fukuo, Y., 1993, Continuous measurements of ground-water seepage using an automatic seepage 

meter: Ground Water, v. 31, no. 4, p. 675–679.

Taniguchi, M., and Fukuo, Y., 1996, An effect of seiche on 

groundwater seepage rate into Lake Biwa, Japan: Water 

Resources Research, v. 32, no. 2, p. 333–338.

Townley, L.R., and Davidson, M.R., 1988, Definition of a capture zone for shallow water table lakes: Journal of Hydrology, v. 104, p. 53–76.

Townley, L.R., and Trefry, M.G., 2000, Surface watergroundwater interaction near shallow circular lakes—Flow 

geometry in three dimensions: Water Resources Research, 

v. 36, no. 4, p. 935–949.

Tyron, M., Brown, K., Dorman, L., and Sauter, A., 2001, 

A new benthic aqueous flux meter for very low to moderate discharge rates: Deep-Sea Research, v. 48, pt. I, 

p. 2121–2146.

Wanty, R.B., and Winter, T.C., 2000, A simple device for measuring differences in hydraulic head between surface water 

and shallow ground water: U.S. Geological Survey Fact 

Sheet FS–077–00, 2 p.

Warnick, C.C., 1951, Methods of measuring seepage loss in 

irrigation canals: University of Idaho, Engineering Experiment Station, Bulletin no. 8, 42 p.

Winter, T.C., LaBaugh, J.W., and Rosenberry, D.O., 1988, The 

design and use of a hydraulic potentiomanometer for direct 

measurement of differences in hydraulic head between groundwater and surface water: Limnology and Oceanography, v. 33, 

no. 5, p. 1209–1214.

Yelverton, G.F., and Hackney, C.T., 1986, Flux of dissolved 

organic carbon and pore water through the substrate of a 

Spartina alteriflora marsh in North Carolina: Estuarine, 

Coastal and Shelf Science, v. 22, p. 255–267.

Zamora, C., 2006, Estimates of vertical flux across the 

sediment—Water interface by direct measurement and using 

temperature as a tracer in the Merced River, California: 

Sacramento, California State University Sacramento, Master’s 

thesis, 90 p.
Hydrogeologic Characterization and

Methods Used in the Investigation of

Karst Hydrology

By Charles J. Taylor and Earl A. Greene

Chapter 3 of

Field Techniques for Estimating Water Fluxes Between 

Surface Water and Ground Water

Edited by Donald O. Rosenberry and James W. LaBaugh

Techniques and Methods 4–D2

U.S. Department of the Interior

U.S. Geological Survey
Contents

Introduction...................................................................................................................................................75

Hydrogeologic Characteristics of Karst..........................................................................................77

Conduits and Springs .........................................................................................................................77

Karst Recharge....................................................................................................................................80

Karst Drainage Basins .......................................................................................................................81

Hydrogeologic Characterization ...............................................................................................................82

Area of the Karst Drainage Basin ....................................................................................................82

Allogenic Recharge and Conduit Carrying Capacity ....................................................................83

Matrix and Fracture System Hydraulic Conductivity....................................................................83

Conduit System Response.................................................................................................................85

Conduit/Fracture Coupling ................................................................................................................87

Water Budget ......................................................................................................................................88

Spring-Discharge Hydrograph Analysis .................................................................................................89

Basin Flow Characteristics ...............................................................................................................89

Basin Hydraulic Properties ...............................................................................................................91

Chemical Hydrograph Separation....................................................................................................91

Precipitation Response Analysis ..............................................................................................................92

Linear Systems Analysis....................................................................................................................92

Lumped-Parameter Models ..............................................................................................................93

Deterministic (Numerical) Modeling ........................................................................................................94

Water Tracing with Fluorescent Dyes......................................................................................................95

Dye-Tracer Test Objectives and Design..........................................................................................96

Dye Injection........................................................................................................................................98

Dye Monitoring and Detection .......................................................................................................100

Use of Charcoal Detectors..............................................................................................................102

Dye-Breakthrough Curve Analysis..........................................................................................................104

Mean Tracer-Dye Residence Time.................................................................................................106

Mean Dye Velocity............................................................................................................................106

Tracer Mass Recovery.....................................................................................................................107

Summary......................................................................................................................................................107

References..................................................................................................................................................107

Figures

1. Block diagram showing physiographic and hydrologic features typical of a 

well-developed karst terrane ...................................................................................................76

2. A, Diagram showing competitive growth of conduits and distortion of hydraulic 

flow field. B, Sequence of development of integrated drainage network due to 

faster growth and breakthrough by primary conduit (1) and subsequent capture 

of flow and linking of secondary conduits (2–4)....................................................................78

3. Photographs showing a variety of physical outlets for karst springs................................79

4. Geologic cross section of a karst basin showing various types of recharge 

sources.........................................................................................................................................80

5. Part of map showing dye-tracing flow paths used to constrain the boundaries 

for two karst spring subbasins .................................................................................................84
6. Subsurface piracy of an 85-square-mile area mapped within the Barren 

River basin 8-digit Hydrologic Unit Code by conduits draining to the adjacent 

Green River basin .......................................................................................................................86

7. Variable response of springs to precipitation........................................................................88

8. Water-quality changes in a karst spring related to allogenic recharge ...........................89

9. Conceptual spring hydrograph showing changes in slope and dominant

flow regime ..................................................................................................................................91

10. Analysis of spring hydrograph of San Marcos Springs in Texas identifying 

the conduit, mixed, and diffuse flow regimes of the karst aquifer.....................................92

11. (A) Conceptual model of the hydrologic components of the upper Lost River

drainage basin in south-central Indiana and (B) four-component hydrograph

separation curves at Orangeville Rise ....................................................................................93

12. Linear system analysis of a karst conduit spring showing the rechargedischarge relation.......................................................................................................................93

13. Predicted and observed (A) discharge at Maramec Spring, Missouri; and 

(B) specific conductance of the spring discharge water....................................................94

14. Calculated output time series and head in an observation well.........................................94

15. Simulation of Barton Spring discharge in the Edwards aquifer, Texas, using 

a lumped and distributed parameter approach.....................................................................95

16. Dye injections..............................................................................................................................99

17. Dye spectral “fingerprints” obtained from use of the synchronous scanning 

method........................................................................................................................................101

18. Some important physical characteristics of a dye-breakthrough curve ........................105

19. Example of dye-breakthrough curves for two dye-tracing tests conducted

in the Edwards aquifer, Texas.................................................................................................105

20. Shapes of hypothetical dye-breakthrough curves affected by changes in 

hydrologic conditions (high flow, low flow) and conduit geometry .................................106

Tables

1. Comparison of various hydrogeologic properties for granular, fractured rock, 

and karst aquifers.......................................................................................................................77

2. Comparison of porosity and permeability measurements in various karst aquifers.......87

3. Range of Unit Base Flow (UBF) values (designated here as normalized base flow 

or NBF) in spring basins in Kentucky.......................................................................................90

4. Water budget calculations for Orangeville Rise spring, southern Indiana.......................90

5. Characteristic values for the slope of the recession curve (α) to determine 

flow regimes in a karst aquifer.................................................................................................92

6. Some commonly used fluorescent dye types, their dye names, and their respective 

Color Index and Chemical Abstracts Service number .........................................................96

7. Emission spectra and detection limits for dyes in water.....................................................96

8. Percent active tracer, and specific gravity, measured for some commonly used 

fluorescent dye tracers ...........................................................................................................102

Introduction

Recharge to and discharge from ground water can be 

measured or estimated over a wide range of spatial and temporal scales in any hydrogeologic setting (National Academy of 

Sciences, 2004). Difficulties often arise in making these measurements or estimates because of insufficient knowledge of the 

processes involved in the transfer of water fluxes, inadequate 

characterization of the hydrogeologic framework in which 

they occur, and uncertainties in the measurements or estimates 

themselves. These difficulties may be magnified considerably in 

complex hydrogeological settings such as karst.

Karst is a unique hydrogeologic terrane in which the 

surface water and ground water regimes are highly interconnected and often constitute a single, dynamic flow system 

(White, 1993). The presence of karst usually is indicated by the 

occurrence of distinctive physiographic features that develop 

as a result of the dissolution of soluble bedrock such as limestone or dolostone (Field, 2002a). In well-developed karst, 

these physiographic features may include sinkholes, sinking (or 

disappearing) streams, caves, and karst springs. The hydrologic 

characteristics associated with the presence of karst also are distinctive and generally include: (1) internal drainage of surface 

runoff through sinkholes; (2) underground diversion or partial 

subsurface piracy of surface streams (that is sinking streams and 

losing streams); (3) temporary storage of ground water within a 

shallow, perched epikarst zone; (4) rapid, turbulent flow through 

subsurface pipelike or channellike solutional openings called 

conduits; and (5) discharge of subsurface water from conduits 

by way of one or more large perennial springs (fig. 1).

A karst aquifer can be conceptualized as an open hydrologic system having a variety of surface and subsurface 

input, throughput, and output flows, and boundaries defined 

by the catchment limits and geometry of conduits (Ford and 

Williams, 1989). The hydrogeologic characteristics of karst 

aquifers are largely controlled by the structure and organization of the conduits, the development of which generally 

acts to short-circuit surface drainage by providing alternative 

subsurface flow paths that have lower hydraulic gradients 

and resistance (White, 1999). Conduits are a third (tertiary) 

form of permeability that is distinctive from, yet interconnected with, the permeability provided by intergranular pores 

(bedrock matrix) and fractures. Because of the interconnection 

of matrix, fracture, and conduit permeability, karst aquifers are 

extremely heterogeneous compared to most granular and many 

fractured-rock aquifers and have hydraulic properties that are 

highly scale dependent and temporally variable (table 1).

Because of these unique hydrogeologic characteristics, 

data requirements for the hydrogeologic characterization of 

karst aquifers are somewhat more intensive and difficult to 

obtain than those for aquifers in most other types of hydrogeologic settings (Teutsch and Sauter, 1991). Wherever karst features are present, the water-resources investigator must anticipate the presence of a flow system that cannot be completely 

characterized by using conventional hydrogeologic methods 

such as potentiometric mapping or hydraulic tests of observation 

wells, by numerical modeling, or by using a study approach that 

treats ground water and surface water as separate hydrologic 

regimes (White, 1993). In karst terranes, a greater emphasis 

must generally be placed on the identification of hydrologic 

boundaries and subsurface flow paths, contributions of water 

from various recharge sources, and the structural and hydraulic 

properties of conduits. The acquisition of these data typically 

requires a multidisciplinary study approach that includes using 

more specialized investigation methods such as water-tracing 

tests and the analysis of variations in spring discharge and water 

chemistry (White, 1993; Ford and Williams, 1989).

This chapter presents an overview of methods that 

are commonly used in the hydrogeologic investigation and 

characterization of karst aquifers and in the study of water 

fluxes in karst terranes. Special emphasis is given to describing the techniques involved in conducting water-tracer tests 

using fluorescent dyes. Dye-tracer testing is a method successfully used in the study of karst aquifers in the United 

States and elsewhere for more than 30 years (Käss, 1998). 

However, dye-tracing techniques generally are not taught 

at the collegiate undergraduate or graduate level, lack a set 

of formalized peer-reviewed procedures, and sometimes are 

difficult to research because case studies often are reported in 

lesser-known publication venues outside the realm of mainstream professional journals (Beck, 2002). Dye-tracer test 

procedures described herein represent commonly accepted 

practices derived from a variety of published and previously 

unpublished sources. Methods that are commonly applied to 

the analysis of karst spring discharge (both flow and water 

chemistry) also are reviewed and summarized.

Chapter 3

Hydrogeologic Characterization and Methods Used 

in the Investigation of Karst Hydrology

By Charles J. Taylor and Earl A. Greene
Ridgetop pond Vertical shaftBase-level stream Base-level spring Non-limestone protective caprock Karst valley Base-level cave passage Cave passages Dry hole Produc

well 

Limestone Bedded ch

Siltstone 

Cave ent

Karst window Sinkhole pond Sinkhole

Vertical scale exaggerated

Illustration 

Figure 1. Physiographic and hydrologic features typical of a well-developed karst terrane (modified from Currens, 2001, Kentucky Geological Surv
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 77

Hydrogeologic Characteristics of Karst

A number of important characteristics of the physical 

hydrogeology of karst are summarized here for the benefit of 

readers less familiar with karst and with the differences between 

karst aquifers and aquifers in other hydrogeologic settings. The 

subject of karst hydrogeology involves a wide variety of geomorphologic, geologic, hydrologic, and geochemical topics that 

are beyond the scope of this report. White (1993, 1999) provides 

good overviews of karst hydrology and the methods typically 

used in its study. Other good sources of information about karst 

include textbooks written by Bogli (1980), White (1988), and 

Ford and Williams (1989); compendiums edited by Klimchouk 

and others (2000), and Culver and White (2004); and the proceedings of various karst conferences held in the United States 

from 1986 to 2005 (National Water Well Association, 1986, 

1988; National Ground Water Association, 1991; Beck, 1995, 

2003; Beck and Stephenson, 1997; Beck and others, 1999; and 

Kuniansky, 2001, 2002, 2005).

Many geological and hydrologic factors influence the 

development of karst, and not all karst features are present or 

developed to the same extent in every karst terrane. The information presented in this report best describes the hydrogeologic 

characteristics of fluviokarst and doline karst, which are common and widespread types of karst terranes in the United States 

(White, 1999). The term fluviokarst is used to describe a karst 

landscape in which the dominant physical landforms are valleys initially cut by surface streams that have been partly or 

completely diverted underground by subsurface conduit piracy 

(Field, 2002a). This type of karst is often typified by carbonate rocks that have low intrinsic permeability and is common 

of karst developed in Paleozoic limestones in the Interior Low 

Plateaus and Appalachian regions of the Eastern United States. 

The term doline karst describes karst landscape in which surface streams are almost entirely absent, and almost all surface 

drainage is captured and drained internally by closed sinkhole 

depressions. This type of karst is typical of carbonate rocks that 

have high intrinsic permeability, such as the Cenozoic limestones 

in the Atlantic coastal regions, and includes the well-known 

Floridan aquifer system. In reality, the physical and hydrologic 

distinctions between fluviokarst and doline karst are not always 

clearly defined, and many karst terranes have characteristics 

common to each.

Conduits and Springs

The most distinctive feature of karst aquifers are the typically dendritic or branching networks of conduits that meander 

among bedding units, join together as tributaries, and increase 

in size and order in the downstream direction (Palmer, 1991). 

In the simplest terms, these conduit networks grow by way of 

a complex hydraulic-and-chemical feedback loop, in which the 

basic steps are: conduit growth and enlargement → increased 

hydraulic capacity → increased discharge → enhanced 

dissolution and physical corrosion → additional conduit 

enlargement → subsurface piracy of flows in smaller conduits 

by the larger conduits. In this process, the largest conduits 

act as master drains that locally alter the hydraulic flow (or 

equipotential) field so as to capture ground water from the 

surrounding aquifer matrix, the adjoining fractures, and the 

smaller nearby conduits (Palmer, 1991, 1999; White and 

White, 1989) (fig. 2). Depending on their sizes (hydraulic 

capacity) and organization (interconnection), conduit networks are capable of discharging large volumes of water and 

sediment rapidly through a karst aquifer (White, 1993). Flow 

velocities in well-developed and well-integrated conduit networks that range on the order of hundreds to thousands of feet 

per day are not uncommon (White, 1988).

Karst springs are the natural outlets for water discharging 

from conduit networks (fig. 3). They typically are developed at a 

local or regional ground-water discharge boundary—that is, at a 

location of minimum hydraulic head in the aquifer—often at or 

near the elevation of a nearby base-level surface stream (White, 

1988). The tributary system of conduit drainage typically 

Table 1. Comparison of various hydrogeologic properties for granular, fractured rock, and karst aquifers (ASTM, 2002).

Aquifer

characteristics

Aquifer type

Granular Fractured rock Karst

Effective porosity Mostly primary, through 

intergranular pores

Mostly secondary, through joints, 

fractures, and bedding plane 

partings

Mostly tertiary (secondary porosity modified 

by dissolution); through pores, bedding 

planes, fractures, conduits, and caves

Isotropy More isotropic Probably anisotropic Highly anisotropic

Homogeneity More homogeneous Less homogeneous Non-homogeneous

Flow Slow, laminar Possibly rapid and possibly 

turbulent

Likely rapid and likely turbulent

Flow predictions Darcy's law usually applies Darcy's law may not apply Darcy's law rarely applies

Storage Within saturated zone Within saturated zone Within both saturated zone and epikarst

Recharge Dispersed Primarily dispersed, with some 

point recharge

Ranges from almost completely dispersedto almost completely point-recharge

Temporal head variation Minimal variation Moderate variation Moderate to extreme variation

Temporal water chemistry 

variation

Minimal variation Minimal to moderate variation Moderate to extreme variation

Reprinted with permission from D 5717–95 Standard Guide for Design of Ground-Water Monitoring Systems in Karst and Fractured Rock Aquifers, copyright 

ASTM International, 100 Bar Harbor Drive, West Conshohocken, PA 19428.
78 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 2. A, Diagram showing competitive growth of conduits and distortion of 

hydraulic flow field: (a) initiation of recharge, (b) change in hydraulic gradient 

in response to propagation of faster growing primary (P) conduit and slower 

growing secondary (S) conduit, (c) primary conduit breaks through to discharge 

boundary, slowing or inhibiting growth of secondary conduit. B, Sequence 

of development of integrated drainage network due to faster growth and 

breakthrough by primary conduit (1) and subsequent capture of flow and linking 

of secondary conduits (2–4). (Modified from Ford, 1999, fig. 8.) (Copyright Karst 

Waters Institute and Dr. Derek Ford, used with permission.)

Top

Bottom

Focused recharge

Focused recharge

1.0

0.8

0.6

0.4

0.2

0

HYDRAULIC HEAD, IN METERS

4

3

2

1

Discharge

a b c

A

B

S

P
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 79

developed in most karst aquifers yields convergent flow to 

a trunk conduit that discharges through a single large spring 

(White, 1999). Many karst aquifers, however, have a distributary 

flow pattern where discharge occurs through multiple spring 

outlets. This distributary flow pattern generally occurs where 

there has been enlargement of fractures and smaller conduits 

located near a stream discharge boundary, where collapse or 

blockage of an existing trunk conduit or spring has resulted 

in shifting of flow and development of alternative flow paths 

and outlets, or where subsurface conduit piracy has rerouted 

preexisting conduit flow (Quinlan and Ewers, 1989).

Traditionally, springs are classified on the basis of discharge per Meinzer’s scale (Meinzer, 1927) and are otherwise 

characterized on the basis of physical appearances and whether 

or not the discharge occurs under artesian or gravity flow (openchannel) conditions (U.S. Geological Survey, 2005). From 

a flow-system perspective, it may be more useful to classify 

karst springs according to their hydrologic function as outlets 

for conduit networks (Worthington, 1991, 1999). In most karst 

aquifers, one or a few perennial springs, called underflow 

springs, carry the base-flow discharge of conduits (Worthington, 

1991). The elevation of the underflow springs exerts much control on the elevation of the water table at the output boundary 

of the karst aquifer, whereas the matrix hydraulic conductivity 

and the conduit hydraulic capacity determines the slope of the 

water table upstream and its fluctuation under differing hydrologic conditions (Ford and Williams, 1989). Other intermittent 

springs, called overflow springs, function as spillover outlets 

during periods of high discharge. Overflow springs are essentially a temporal form of distributary discharge. As conduits 

evolve through time and as base levels and water tables are lowered, the upper parts of the karst aquifer may be progressively 

drained and higher level conduits abandoned (Hess and White, 

1989). During high-flow conditions, these higher level conduits 

may be reactivated and discharge through overflow springs now 

located at the outlets of former underflow springs.

Figure 3. Photographs showing a variety of physical outlets for karst springs: A, Orangeville Rise, southern Indiana; B, Whistling Cave 

Spring, southern Indiana; C, Rocky Spring, central Kentucky; D, Head-of-Doe-Run Spring, central Kentucky. (Photographs by Charles J. 

Taylor, U.S. Geological Survey.)

B

A

D

C
80 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 4. Geologic cross section of a karst basin showing various types of recharge sources: concentrated versus diffuse, 

and autogenic (recharge that originates as precipitation falling directly on karstic rocks) versus allogenic (recharge that 

originates as precipitation falling on nonkarstic rocks). Water flows through the unsaturated zone via (1) diffuse flow through 

soil or unconsolidated surface materials, (2) concentrated flow through solution-enlarged sinkhole drains, (3) diffuse 

infiltration through vertical fractures, and (4) diffuse infiltration through permeable rock matrix. Subterranean conduits 

shown as solid black are filled with ground water. (Modified from Gunn, 1986, used with permission.)

Diffuse autogenic recharge 

(may be concentrated in 

subcutaneous zone)

Concentrated 

autogenic recharge from 

closed depressions

Diffuse allogenic

recharge through

permeable cap rock

Concentrated allogenic

recharge from

stream-sink

Integrated

unsaturated flows

Percolation

stream

3

2

3

1

3

3

4

4

Karst Recharge

Karst terrane is unique in having multiple sources of 

recharge that vary considerably in terms of water residence 

time and in the timing and amounts of water contributed to the 

conduit network. Sources of karst recharge are categorized as 

concentrated or diffuse, and as either autogenic or allogenic

depending, respectively, on whether the recharge originates as precipitation falling on karstic or nonkarstic terrane 

(Gunn, 1983). These distinctions are important because the 

relative proportion of concentrated to diffuse recharge generally dictates the distribution and linking together of conduits, 

and the timing and relative contributions of water fluxes from 

allogenic and autogenic sources significantly affects the variability in spring discharge and water chemistry (Ford and 

Williams, 1989).

A cross-sectional diagram of the major sources of 

recharge that contribute to a typical karst flow system is shown 

in figure 4. A major source of concentrated allogenic recharge 

to many karst aquifers is water contributed by sinking or losing 

streams that originate as normal gaining streams in nonkarstic 

borderlands. A major source of concentrated autogenic recharge 

is surface runoff funneled into sinkhole depressions, which 

may drain rapidly to the subsurface through throatlike openings 

called swallets or may drain relatively slowly by percolation 

through a mantle of soil or alluvium. Diffuse allogenic recharge 

may be contributed by interaquifer transfer of water from 

nonkarstic aquifers, but a more common source is water that 

drains down the walls of unsaturated (vadose) zone shafts—

vertical or near-vertical conduit passages—where karstic 

rocks are overlain by nonsoluble caprocks such as sandstone 

(Gunn, 1983).
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 81

In typical studies of karst hydrology, the understandable 

focus placed on the characterization of concentrated recharge 

tends to overshadow the fact that most recharge to karst 

aquifers is contributed by diffuse autogenic recharge—that is, 

by infiltration through soil—as it is in most other hydrogeologic settings. In a study in Missouri, Aley (1977) estimated 

that the quantity of water contributed to a karst aquifer from 

diffuse areal recharge was approximately four times greater 

than that contributed by all concentrated recharge sources and 

almost twice that contributed by sinkholes and losing streams 

combined. Most sinkhole swallets have active inflow only during periods of heavy surface runoff when soil and macropore 

infiltration capacity is exceeded and, depending on antecedent 

moisture conditions, the inflow of concentrated recharge by 

way of swallets may not occur during many storms.

A particularly important source of recharge and storage 

in most karst aquifers is the epikarst—a zone of intensely 

weathered, fractured, and solution-modified bedrock located 

near the soil-bedrock contact (Williams, 1983). The thickness and physical hydrogeologic properties of the epikarst 

are highly variable within and among karst terranes because 

epikarst development is dependent on stratigraphic variability; 

bedrock porosity, permeability, and solubility; fracture density; and intensity of weathering. In terms of hydrology, the 

epikarst functions generally as a leaky perched aquifer zone, 

providing relatively long-term, diffuse autogenic recharge to 

conduits (Klimchouk, 2004). Much of the base-flow discharge 

from karst aquifers to springs and surface streams is water 

contributed from storage in the epikarst. Chemical hydrograph 

separation studies have indicated that flushing of water from 

the epikarst may contribute as much as 50 percent of the water 

discharging from springs during storms (Trc ́ek and Krothe, 

2002). Much research has been devoted to the development 

and hydrologic functioning of the epikarst; however, it remains 

one of the more poorly understood recharge components of 

karst aquifers (Aley, 1997; Jones and others, 2004).

Karst Drainage Basins

In typical hydrogeologic studies, a fundamental mapping 

unit—usually defined by the ground-water basin—is used to 

characterize the spatial and temporal properties of the aquifer and to construct a conceptual model. For a karst aquifer, 

the traditional concept of the term “ground-water basin” 

is somewhat of a misnomer in that it minimizes the highly 

interconnected nature of surface and subsurface waters and the 

role of concentrated stormwater runoff as a significant source 

of recharge. A more appropriate term, and conceptual model, 

for most karst aquifers is the karst drainage basin (or karst 

basin)—a mapping unit defined by the total area of surface 

and subsurface drainage that contributes water to a conduit 

network and its outlet spring or springs (Quinlan and Ewers, 

1989; Ray, 2001). Karst basins differ from conventionally 

defined ground-water basins—that is, the local ground-water 

basins described by Toth (1963)—in the following respects:

•	 Karst basin boundaries do not always coincide with 

topographic drainage divides, and discharge may or 

may not always be to the nearest surface stream.

•	 Recharge near the basin boundaries may flow in a 

radial or semiradial direction into adjacent basins 

drained by other underflow springs, and the divides 

between basins may be indistinct and may shift with 

changing hydrologic conditions.

•	 Direct injection of concentrated stormwater runoff and 

subsurface piracy of surface streamflows constitute a 

significant portion of the recharge to the basin.

•	 Most of the active flow is concentrated in the core 

of the basin, which consists of the conduit network, 

and is characterized by pipe-full or open-channel 

hydraulics. Vertical or cascading flow may be significant (Thrailkill, 1985).

•	 Hydraulic gradients, the number of active conduit 

flow routes, and directions of ground-water flow may 

change rapidly with changing hydrologic conditions.

•	 Directions of ground-water flow do not always conform with the maximum hydraulic gradient inferred by 

water-level measurements in wells.

•	 The contributing area and volume of discharged 

subsurface water changes over time as conduit development, hydraulic capacity, and subsurface piracy 

increases. In addition, the aquifer carries a substantial 

sediment load that is constantly changing and can 

alter flow routes and hydraulic properties of conduits 

(White, 1988; Dogwiler and Wicks, 2004).

Ray (1999, 2001) proposed that karst basins can be 

broadly categorized into three functional hydrologic groups 

on the basis of the hydraulic capacity of their conduit networks 

and their dominant recharge source (allogenic or autogenic). 

The three basin groups are defined as:

•	 Overflow allogenic basins—basins in which the trunk 

(master) conduit draining the basin is recharged 

mostly by subsurface piracy of a surface stream(s), 

but because of limited hydraulic capacity, the surface 

channel is maintained as a losing stream reach or as 

an intermittent, storm-overflow route.

•	 Underflow allogenic basins—basins in which the 

hydraulic capacity of the trunk conduits has increased 

to the point that the surface flow is completely diverted 

underground through streambed swallets, and the surface valley becomes blind.

•	 Local autogenic basins—basins in which all surface flow has been captured by subsurface piracy, 

and the trunk conduit is recharged almost exclusively by infiltration through the soil and internal 

sinkhole drainage.
82 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

These basin categorizations apply best to shallow, unconfined karst aquifers in fluviokarst settings, but also describe 

basins in doline karst and in deeper partly confined karst aquifers such as the Madison Limestone aquifer (Greene, 1997) in 

South Dakota, which is characterized by overflow allogenic 

basins recharged by sinking streams draining a structurally 

uplifted recharge area. A progressive sequence of karst basin 

development—from overflow allogenic to underflow allogenic 

to local autogenic—may occur in many karst terranes over 

geologic time as karstification and subsurface piracy of surface 

streams increases (Smart, 1988; Ray, 2001).

Hydrogeologic Characterization

As in other complex hydrogeologic settings, a proper 

hydrogeologic characterization of karst drainage basins is the key 

to understanding and estimating water fluxes. As applied within 

the framework of a karst conceptual model, this requires the 

acquisition of data needed to characterize the extent and overall 

effects of conduit-dominated flow, multiple discrete inputs and 

outputs for water, and spatial and temporal variability in recharge, 

storage, and flow. Water-tracing tests, typically done using 

fluorescent dyes, are the most effective means of determining 

subsurface conduit connections between karst drainage features 

such as sinkholes and springs, directions of ground-water flow 

in the karst aquifer, boundaries of karst ground-water basins, 

and the hydraulic properties of conduits (Mull and others, 1988; 

White, 1993). The analysis of spring discharge hydrographs and 

temporal variations in the chemical or isotopic composition of 

spring water provide data needed to characterize the recharge, and 

storage and discharge functions occurring in karst aquifers and to 

provide additional insights into the structure of conduits at basinto-regional field scales (Ford and Williams, 1989; White, 1993).

Other, more conventional hydrogeologic data-collection 

methods—including those described in other chapters of this 

report—also may be used in the study of karst aquifers if these 

methods are applied within the framework of a karst conceptual model. Careful consideration must be given to the field 

scale of collected hydrologic measurements and to whether 

the measurements obtained by use of a particular method are 

representative of the conduit-dominated flow components of 

the aquifer, the aquifer matrix or nonconduit flow component, 

or a composite of both.

In addition to the topographic, structural, and stratigraphic 

characteristics that are necessary to define the physical hydrogeologic framework, White (1999) proposes six basic hydrologic 

properties needed for the evaluation of karst basins: (1) the area 

of the karst basin, (2) allogenic recharge, (3) conduit carrying 

capacity, (4) matrix and fracture system hydraulic conductivity, 

(5) conduit system response, and (6) conduit/fracture coupling. 

A water budget is suggested here as a seventh additional characteristic for evaluation. Information collected about each of these 

seven karst basin features will contribute to the identification and 

estimation of fluxes between surface water and ground water in 

karst terranes.

Area of the Karst Drainage Basin

Various methods have been used to estimate the recharge 

or contributing areas of karst springs (Ginsberg and Palmer, 

2002), but dye-tracer tests provide the most effective means 

of identifying the point-to-point connections between flow 

inputs (sinkholes or sinking streams) and outputs (springs) 

needed to actually define the boundaries of karst drainage 

basins (White, 1993; Ray, 2001). Dye-tracer tests can be 

done at multiple input sites by injecting different fluorescent 

dyes either simultaneously or sequentially. As tracer-inferred 

ground-water flow directions are determined and the number 

and distribution of tracer-determined flow paths increase, the 

boundaries, approximate size, and shape of the basin under 

study can be delineated with increasing levels of confidence. 

To fully delineate the boundaries of the area contributing recharge to a particular spring, dye-tracer tests need 

to be planned and conducted in strategic locations so that 

the results obtained “push” the point-to-point connections 

established between the spring and its contributing inputs 

(for example, sinkholes) toward the anticipated locations of 

subsurface drainage divides. The presence of these drainage 

divides are inferred where the trajectories of plotted dyetracer flow paths indicate a divergence in subsurface flow 

directions, that is, identify areas where subsurface flows are 

being routed to springs draining other adjacent karst basins. 

The geographic distribution of these inferred subsurface drainage divides constrains the boundaries of the karst basin under 

study (fig. 5).

Tracer-inferred flow paths can be plotted as straight 

lines between input and resurgence sites, or preferably, as 

curvilinear vectors that depict a tributary drainage system 

more visually representative of the natural conduit network 

(Ray, 2001). Other hydrogeologic mapping data such as cave 

surveys or contoured water-level maps can be used as an 

aid in the planning and interpretation of dye-tracer tests; for 

example, the locations of major ground-water conduits often 

are correlated with the positions of apparent troughs in the 

potentiometric surface or water table, which are thought to 

represent a locus of maximum ground-water flow (Quinlan 

and Ewers, 1989). Karst mapping studies that illustrate various 

applications of these techniques include those of Crawford 

(1987), Mull and others (1987), Vandike (1992), Bayless and 

others (1994), Schindel and others (1995), Imes and others 

(1996), Jones (1997), Taylor and McCombs (1998), and 

Currens and Ray (1999).

Dye-tracer tests have routinely shown that conduit flow 

paths commonly extend beneath topographic drainage divides 

and, in some places, beneath perennial streams, and that surface 

runoff draining into sinkholes or sinking streams in one topographic basin (watershed) may be transferred via subsurface 

flow routes into adjacent topographic basins (Ray, 2001) 

(fig. 6). In karst terranes, mapping of the contributing areas 

of springs and surface streams, identification and estimation 

of water fluxes and, in particular, estimation of water budgets 

for either surface or subsurface drainage basins, are critically 
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 83

dependent on identifying and delineating the areas that indicate 

this “misbehaved drainage” (White and Schmidt, 1966; Ray, 

2001). Dye-tracer tests are the most reliable method of obtaining this information. For example, dye-tracer tests were used 

to conclusively demonstrate that the USGS Hydrologic Unit 

(watershed) boundaries delineated for the Barren River basin 

in central Kentucky using topographic drainage divides encompass approximately 220 square kilometers (85 square miles) of 

surface drainage that actually contributes water to the adjacent 

Green River basin via subsurface conduits (Ray, 2001) (fig. 6).

Allogenic Recharge and Conduit 

Carrying Capacity

As previously noted, a significant component of recharge 

to underflow and overflow allogenic karst basins is the water 

contributed by subsurface piracy of surface streams, and it 

is this concentrated allogenic recharge that largely influences the discharge and water-chemistry changes indicated 

by karst springs during and after storms. Quantifying the 

allogenic recharge subbasin area and the sum of the inputs 

from individual sinking or losing streams defines an important 

characteristic of the hydrology of a karst basin. Geographic 

Information System (GIS) technology provides a convenient 

way of delineating the catchment areas of all sinking or losing 

streams that contribute to a karst basin and of estimating the 

relative proportion of allogenic recharge subbasin area to autogenic recharge (sinkhole-dominated) subbasin area (Taylor and 

others, 2005). In theory, all of the allogenic recharge contributed to a karst basin can be measured by synoptic gaging of 

discharge in the stream channels directly above the locations 

of terminal swallow holes. When evaluated with discharge 

measurements from the basin’s outlet springs, the measured 

allogenic inputs provided by each sinking or losing stream can 

be used to evaluate conduit-carrying capacity (White, 1999) in 

the following manner:

In underflow allogenic basins, the hydraulic capacities of 

the conduits are defined by the following relation:

Qc > Qa(max) (1)

where

Qc is the carrying capacity of the conduits

and

Qa (max) is the maximum discharge of the surface 

stream(s) contributing recharge to the 

conduits.

In this particular instance, the carrying capacity of the conduit 

network always exceeds the maximum input contributed by 

the allogenic stream recharge, and surface flows are completely diverted underground by one or more swallow holes 

shortly after crossing onto karstic bedrock. This case describes 

a classic sinking stream.

In overflow allogenic basins, the carrying capacities of 

the conduits are defined by one of two relations (eqs. 2 or 3):

Qa(base) > Qc, (2)

where

Qa (base) is the base-flow discharge of the allogenic 

surface stream.

In this case, the carrying capacity of the conduits cannot 

accommodate the base-flow discharge of the allogenic stream, 

and perennial surface flow occurs in the channel despite flow 

losses through streambed swallow holes. This case describes a 

classic losing stream.

Qa(max) > Qc > Qa(base). (3)

In this case, the carrying capacity of the conduits can accommodate all of the base-flow discharge from the allogenic 

stream, but stormflow discharge often exceeds the capacity of 

the conduits, overtops swallow holes, and results in continuation of flow down the channel. This case describes an intermittent sinking stream, often characterized as a “dry-bed stream” 

(Brahana and Hollyday, 1988). The reactivation of swallow 

holes as sink points often occurs in a successive manner as 

surface flow overtops upstream swallow holes first and reaches 

or overtops the farthest downstream swallow holes only during 

the largest storms (George, 1989).

White (1999) makes the interesting suggestion that determining the critical flow threshold when Qa

 = Qc would be a 

meaningful way of characterizing conduit permeability; however, it would require gaging the discharge in sinking streams 

above the terminal swallow holes at the exact time that the 

swallow holes are filled and overtopped. There are practical 

difficulties involved in obtaining such measurements, not only 

with regard to the timing of the measurements, but because 

flow in the channels of many sinking streams often is lost 

progressively through a series of swallow holes; for example, 

the Lost River basin of southern Indiana (Bayless and others, 

1994), or because clogging of the swallow holes with sediment 

or debris is a factor that controls the rate of inflow (Currens 

and Graham, 1993).

Matrix and Fracture System 

Hydraulic Conductivity

Because of combined permeability provided by matrix, 

fracture, and conduit-flow components, the timing and amount 

of response to hydraulic stresses varies greatly from place 

to place within a karst aquifer. Investigation of the hydraulic conductivity of the matrix and fracture components is 

typically performed with conventional hydrogeologic tools. 

Matrix permeability can be determined using laboratory 

permeability tests done on representative rock core samples. 

Fracture hydraulic conductivity is best determined using 
84 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

7

7

0 1 2 3 4 5 KILOMETERS

0 1 2 3 4 5 MILES

625

650

600

600

625

650

675

675

650

625

600

600

625

650

675

675

700

700

700

700

675

650

650

675

675

650

625

600

37°56'40"

86°10' 86°00'

37°45'

Base from U.S. Geological Survey Digital Data, 1:24,000, 1996

Mercator Projection

KENTUCKY

Study area
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 85

straddle-packer hydraulic tests and borehole flow meters 

(Sauter, 1991). Conventional aquifer tests (time-drawdown, 

distance-drawdown, or slug tests) provide a measurement of 

the integrated local matrix and fracture system transmissivity. 

Borehole geophysical methods, including cross-borehole tests, 

also provide valuable data to assist with permeability and flow 

characterization at local to subbasin scales (Paillet, 2001).

Analysis of karst aquifer test data using conventional 

Darcian analytical methods may provide erroneous results, 

and special consideration should be given to the possible 

effects of slow-flow and quick-flow karst components on 

the hydraulic responses represented by the well-hydraulic 

test data. Streltsova (1988) reviews aquifer-test methods best 

suited to investigations of heterogeneous aquifers such as 

karst. If the test well penetrates large solutional openings or 

conduits, the hydraulic conductivity (or transmissivity) and 

storage coefficients of these should be evaluated separately 

from those of fractures (Greene and others, 1999).

Comparative studies of hydraulic properties measured 

in different karst aquifers have shown that, regardless of the 

range of porosity measured in the aquifer matrix, conduits 

typically account for less than 1 percent of the porosity of the 

aquifer, but more than 95 percent of the permeability (table 2) 

(Worthington and others, 2000). As in studies of many 

fractured rock aquifers, there is a general tendency for measured hydraulic conductivities to increase with increasing field 

scale (Sauter, 1991). Typically, the distribution of hydraulic 

conductivity and other properties is related to lithostratigraphic 

facies changes or other physical changes in the characteristics 

of the bedrock matrix (Rovey and Cherkauer, 1994).

Conduit System Response

Conduit system response may be evaluated using: 

(1) quantitative water-tracing tests to determine traveltime and 

tracer-breakthrough characteristics, (2) recession analysis of 

spring discharge hydrographs (White, 1999), (3) evaluation of 

the ratio between peak storm discharge and base-flow discharge 

(Qmax/Qbase) of karst springs, (4) chemical hydrograph separation, 

and (5) hydrologic pulse analysis—analysis of changes in spring 

discharge and water-quality constituents in response to storms 

(Ryan and Meiman, 1996; Katz and others, 1997).

Early studies of the variation in spring discharge and water 

chemistry led to the suggestion that karst springs and aquifers 

could be categorized along a hydrologic continuum defined by 

conduit-dominated and diffuse-dominated end members (Shuster 

and White, 1971; Atkinson, 1977; Scanlon and Thrailkill, 1987) 

with the observed hydrologic response differing according to 

the proportion of conduit-to-nonconduit permeability (fig. 7). 

So-called conduit-dominated karst springs typically exhibit 

rapid changes in discharge and wide-ranging changes in water 

chemistry in response to precipitation input (fig. 8). In contrast, 

so-called diffuse-dominated karst springs respond more slowly 

to precipitation input and exhibit more buffered, gradual changes 

in discharge and water chemistry. These distinctions seem to be 

applicable in a broadly descriptive context and are still used as a 

convenient way of characterizing karst flow systems.

More recent studies have indicated that karst spring 

discharge and water chemistry responses are influenced by 

temporal variability in the proportion of recharge contributed 

from diffuse and concentrated sources (White, 1999), and 

by the timing and volume of water contributed from conduit, 

fracture, and matrix flow components that reflect the range of 

transmissivities present in the karst basin or aquifer (Doctor 

and Alexander, 2005). Many karst springs and aquifers are 

observed to exhibit a dual or triple hydrologic response to 

precipitation defined by: (1) an initial rapid flow response 

created by water transmission in conduits greater than 5 to 

10 millimeters in diameter where velocities generally exceed 

0.001 meter per second, followed by (2) a secondary, slower 

flow response created by water transmission in intergranular 

pore spaces, smaller aperture fractures, and solutional openings within the aquifer matrix where velocities are less than 

0.001 meter per second (Worthington, Davies, and Ford, 

2000), and (3) a transitional response period between these 

Figure 5 (above and facing page). Part of map showing dyetracing flow paths (red curvilinear vectors) used to constrain 

the boundaries for two karst spring subbasins (orange, yellow 

shading). Dashed blue lines are water-table contour lines, which 

provide additional information useful in mapping the basin 

boundaries and interpreting subsurface flow paths (modified from 

Taylor and McCombs, 1998).

600

Northern ground-water basin

Southern ground-water basin

Inferred potentiometric-surface contour—Shows altitude

at which water level is expected to stand in tightly cased

wells completed exclusively in the St. Louis Limestone.

Contour interval 25 feet. Datum is North American Vertical

Datum of 1988 (NAVD 88).

Ground-water basin boundary—Appropriate location of 

ground-water divide defined by topographic, geologic, and

hydrologic features that influence the direction of groundwater flow.

Dye flow path—Shows inferred route of dye tracer in karst

aquifer and confirmed hydraulic connection between dyeinjection site and dye-recovery site. Dashed line indicates

intermittent flow route to an overflow spring. Number 

indicates dye-tracing test.

Intermittent stream and terminal sink point (swallow hole)

Well

Dye-injection site

Dye-recovery site

Perennial (underflow) spring

Intermittent (overflow) spring

Karst-window—Perennial spring and sinking stream

EXPLANATION

Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 87

two. Accordingly, the alternative terms “quick flow,” “slow 

flow,” and “mixed or intermediate flow” now are used often to 

describe the range of hydrologic responses exhibited by a karst 

spring or aquifer (White, 1993). Various methods of spring 

hydrograph analysis, summarized later in this chapter, may 

be applied to investigate and quantify these changes in karst 

hydrologic responses.

One simple method of quantifying and evaluating the 

“flashiness” of the conduit system response is to determine 

the ratio of maximum peak-flow to base-flow spring discharge 

(Qmax/Qbase); it is a function of storm intensity and conduit organization or interconnectivity (White, 1993). Springs dominated 

by a quick-flow response typically exhibit Qmax/Qbase ratios in the 

range of 40 to 100, whereas ratios of about 1 to 3 and 7 to 10, 

respectively, are exhibited by springs dominated by a slow flow 

response and by intermediate or mixed flow response (White, 

1993). The timing of these changes in hydrologic response 

depends on the size of a karst basin, the distances between 

flow inputs and outputs, and on the internal organization of its 

conduit network (White, 1993). The response time, t

r

, determined by fitting an exponential function to the recession limb 

of the spring hydrograph, also seems to indicate a wide range in 

values that cluster into distinctive groups characteristic of each 

hydrologic response type.

Table 2. Comparison of porosity and permeability measurements in various karst aquifers (after Worthington, 1999).

[%, percent; m/s, meter per second]

Karst area Porosity (%) Hydraulic conductivity (m/s)

Matrix Fracture Conduit Matrix Fracture

Smithville, Ontario 6.6 0.02 0.003 1×10–10 1×10–5

Mammoth Cave, Kentucky 2.4 0.03 0.06 2×10–11 1×10–5

Devonian Chalk, England 30 0.01 0.02 1×10–8 4×10–6

Nohoch Nah Chich, Yucatan, Mexico 17 0.1 0.5 7×10–5 1×10–3

Figure 6 (above and facing page). Subsurface conduit piracy 

of surface drainage from part of the Barren River watershed to 

springs discharging to the Green River watershed. (Courtesy of 

Joe Ray, Kentucky Division of Water, map modified from Ray and 

Currens, 1998.)

Conduit/Fracture Coupling

Under normal base-flow conditions, conduits act as lowhydraulic resistance drains that locally alter the hydraulic flow (or 

equipotential) field so as to capture ground water from the surrounding aquifer matrix and adjoining fractures (White, 1999). The 

flux of water between conduit-flow and nonconduit-flow components is a complex head-dependent process and may be reversible when conduits fill completely and pressurize under certain 

storm-flow conditions. Water flux reversal also can be induced 

by backflooding of surface streams, wherein surface water enters 

conduit passages by way of underflow and overflow springs and 

results in hydraulic damming. In either instance, the injection of 

water from the conduits back into the aquifer matrix constitutes 

an unusual type of aquifer recharge and bank storage, which has 

been well documented, for example, in the Green River-Mammoth 

Cave karst aquifer system in Kentucky (Quinlan and Ewers, 1989). 

As stormwater or flood pulses are drained rapidly through the 

conduits, spring discharge returns to base-flow conditions, and the 

normal flux resumes as the dominant source of recharge shifts to 

water contributed from longer term storage in the epikarst, bedrock 

matrix, fractures, and smaller tributary conduits.

The effectiveness of the coupling between conduit and 

fracture components, combined with the hydraulic conductivity 

of the matrix/fracture system, control the rate of movement of 

water into and out of storage after storms or floods and during 

base-flow conditions (White, 1999). The conduit/fracture coupling can be evaluated by: (1) deconvolution of spring hydrographs, (2) comparisons of storm-related hydrograph response 

in springs or observation wells in the manner described by 

Shevenell (1996), and (3) evaluation of unit base flow.

The unit base flow (UBF), or base-flow discharge per 

unit area, is a particularly useful measurement derived from the 

concept that surface-stream watersheds of similar size (area) 

located in similar hydrogeologic settings and climates will generate approximately equal quantities of base-flow runoff (Quinlan 

and Ray, 1995). Applied to karst basins, the UBF represents 

the amount of water discharged from long-term ground-water 

storage, as controlled by the coupling between the conduits and 

the diffuse-flow component. Its value is best calculated by using 

dry-season, base-flow spring discharge measurements (Quinlan 

and Ray, 1995). Table 3 lists the range of UBF values calculated 

for several spring basins in Kentucky. UBF values are useful in 

estimating the basin areas of springs in similar hydrogeologic settings whose basin boundaries are unknown or untraced, and help 

identify anomalous recharge or storage characteristics for a spring 

basin under study (White, 1993; Quinlan and Ray, 1995).

EXPLANATION

Cave stream

Karst window

Overflow spring

Perennial spring

Swallet

Water well

Other injection

Sinking stream

Surface overflow

Inferred ground-water flow path

Inferred ground-water flow path

Area of conduit-pirated surface drainage

Hydrologic unit (surface watershed) boundary

Dye injection or 

monitoring sites
88 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Water Budget

Water budgets typically are written with the 

instantaneous flows integrated over a specified period of time, 

which can be a water year (season to season), a season, the duration of a single storm, or any other period (White, 1988). Published examples of water-budget calculations for karst aquifers 

include Bassett’s (1976) study of the Orangeville Rise spring 

basin in south-central Indiana, and Hess and White’s (1989) 

study of the spring-fed Green River within the boundaries of 

Mammoth Cave National Park in Kentucky. Other examples 

are discussed by Milanovic ́ (1981a, b) and Padilla and others 

(1994). Equations may take a variety of forms depending on the 

purpose and the hydrologic terms that can be estimated or must 

be evaluated. A simple, conventional water-budget equation for 

a karst basin or aquifer may be written in the form:

I = O + ET + S, (4)

where

I is precipitation,

O is basin or spring discharge,

ET is evapotranspiration, 

and

S is change in ground-water storage 

(Bassett, 1976).

Using this equation, a water balance can be obtained by summing the values for O, ET, and S and subtracting the resulting value from I. The results are expressed as the percentage 

of rainfall unaccounted for (positive I values), or in excess of 

the balance (negative I values) (table 4).

A water-budget equation also can be written to express 

the change in storage occurring as a result of a storm:

Qi – Qo = ± V/t, (5)

where

Qi is the total inflow or recharge contributed 

by the storm,

Qo is the outflow discharge,

V is the change in storage,

and

t is the time period of the storm (Ford and 

Williams, 1989).

Antecedent precipitation and soil-moisture conditions are 

influential in determining the magnitude of Qi

and Qo.

More complex water-budget equations can be developed 

to include additional karst hydrologic factors. White (1988), 

for example, describes how a water budget developed for an 

allogenic overflow karst basin might include terms for the input 

by sinking streams (the allogenic recharge), internal runoff 

(sinkhole drainage), diffuse infiltration (through soil, epikarst, 

and bedrock matrix), and positive or negative changes in 

ground-water storage. In these types of calculations, allogenic 

Figure 7. Variable response of springs to precipitation. Copperhead Spring hydrograph shows rapid conduit-dominated 

flow response. Langle Spring hydrograph shows slow diffuse-dominated flow response. These are related to the relative 

proportion of conduit permeability to nonconduit permeability (courtesy of Van Brahana, University of Arkansas).

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

FLOW, IN GALLONS PER MINUTE

8.5

8

7.5

7

6.5

6

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

PRECIPITATION, IN MILLIMETERS

Q = 15749.2 gallons per minute in 01/04/98 at 6:00 p.m.

Copperhead Spring

Q = 972.86 gallons per minute in 01/05/98 at 6:40 a.m.

Langle Spring

1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12 1/13 1/14 1/15 1/16 1/17

DATE 1998

EXPLANATION

Langle Spring

Copperhead Spring

Precipitation
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 89

recharge from sinking or losing streams can be directly measured, at least in theory, and estimation of the contribution of 

autogenic (sinkhole) recharge is more problematic. Change in 

storage typically is estimated from analysis of spring recession 

hydrographs using the methods described by Kresic (1997), or 

estimated in terms of net head change in the aquifer on the basis 

of water-level measurements from observation wells.

Spring-Discharge 

Hydrograph Analysis

Spring discharge represents an integration of the various processes that govern recharge, storage, and throughflow in a karst 

basin upstream from its outlet (Kresic, 1997). Analysis of the 

spring-discharge hydrograph makes it possible to obtain valuable 

insights into hydraulic stresses acting on the basin, to evaluate 

basin flow characteristics, and to estimate average basin hydraulic 

properties (Bonacci, 1993; Baedke and Krothe, 2001; Pinault 

and others, 2001). A wide variety of graphical, time-series, and 

spectral analysis techniques have been applied that are beyond the 

scope of discussion of this chapter. Many of these techniques are 

reviewed by White (1988) and Ford and Williams (1989).

Analysis of the recession period of the spring discharge 

hydrograph is one of the simpler and more useful methods to 

apply to karst studies because it provides information about 

the volume of water drained from the karst basin over time 

after peak flows and changes in the rate of discharge that may 

indicate thresholds and limits in aquifer flow regimes (Doctor 

and Alexander, 2005). A step-by-step review of the recession 

analysis technique is presented by Kresic (1997). Its application to the determination of karst basin flow and hydraulic 

characteristics is summarized here.

Basin Flow Characteristics

Interpretation and analysis of a spring hydrograph 

assumes that: (1) the discharge of the spring is controlled by 

input events such as a high-intensity precipitation event or a 

recharge event at a sinking stream, and (2) the shape of the 

hydrograph is controlled by flow through various pathways 

that have different conductivities and velocities (Milanovic ́, 

1981b). By using recession analysis, it is possible to identify whether the overall basin flow characteristics are dominated by quick flow (conduit-dominated flow), slow flow 

Figure 8. Water-quality changes in a karst spring related to allogenic recharge: Precipitationstormwater runoff causes a rise in turbidity and a decrease in specific conductance prior to and during 

peak spring discharge. After passage of the stormwater recharge pulse, conductivity increases as the 

spring discharge returns to base flow (discharge of water contributed from storage by the slow diffuseflow karst component). (Courtesy of James Currens, Kentucky Geological Survey.)

Turbidity

Discharge

Conductivity

Precipitation

4.84

centimeters

2.27

centimeters

0

100

200

300

400

500

600

700

0.0

0.5

1.0

1.5

2.0

PRECIPITATION, 

IN CUBIC METERS 

PER 10 MINUTES

SPECIFIC CONDUCTIVITY

AND TURBIDITY

0

2

4

6

8

10

12

14

16

18

20

0.0

0.5

1.0

1.5

2.0

DISCHARGE FROM SPRING, 

IN CUBIC METERS PER SECOND

PRECIPITATION,

IN CUBIC METERS 

PER 10 MINUTES

July 29, 1996

July 30, 1996

July 31, 1996
90 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Table 3. Range of Unit Base Flow (UBF) values (designated here as normalized base flow or NBF) in spring basins in Kentucky 

(modified from Quinlan and Ray, 1995).

[cfs, cubic feet per second]

Autogenic

recharge group Spring name

Spring

identification

number

Basin area

(miles2

)

Summer

base flow

(cfs)

Normalized

base flow, NBF

(cfs/mile2

)

Geometric

mean NBF

(cfs/mile2)

1. With up to 25 percent allogenic 

recharge from sandstone-capped 

ridgetops or near-surface, leaky, 

chert aquitard

Lavier Blue Hole 21 10.2 2.1 0.21

Garvin-Beaver 22 7.2 1.7 0.24

Echo River -- 8.8 1.8 0.21 0.20

Lost River -- 55.2 12.0 0.22 (0.21)

Pleasant Grove -- 16.1 2.5 0.16

Shakertown -- 19.0 3.6 0.19

2. With significant allogenic recharge 

from carbonate terrane

Gorin Mill 23 152 25.1 0.17

Turnhole 3 90.4 14.3 0.16 0.17

Graham 21 122 20.8 0.17

3. With locally thick, areally significant 

sand and gravel cover

Rio 13 5.2 4.7 0.91

Rio 13 6.5 4.7 0.72

McCoy Blue 1 36.1 12.3 0.34

Roaring 6 10.8 11.9±1 1.19 0.70

Roaring 1.01 (0.75)

Johnson 7 17.5 11.0 0.63

Jones School 19 3.9 2.3 0.59

Jones School 19 2.9 2.3 0.79

4. With much interbedded shale, 

Bluegrass Region

Royal -- 25.0 2.8 0.11

Russell Cave -- 6.4 1.0 0.15 0.11

Garretts -- 7.4 0.5 0.07

(diffuse-dominated flow), or mixed flow, and to evaluate the 

timing and magnitude of changes in spring discharge that correspond to changes between these flow regimes (fig. 9).

 Analysis of a spring discharge hydrograph to determine 

the flow regimes of the karst basin is done through methods 

presented by Rorabaugh (1964) and Milanovic ́ (1981a,b). 

Even though these methods are based on Darcian theory, the 

hydrograph analysis methods have been successfully applied 

to many studies of karst basins (Baedke and Krothe, 2001; 

Shevenell, 1996; Padilla and others, 1994, Sauter, 1992; and 

Milanovic ́, 1981a). The method of characterizing karst flow 

regimes is based on the equation below, whereby the recession curves of spring hydrographs are analyzed to calculate 

the value of α, the recession slope: 

Qt = Qo e –α(t–to) (6)

where

t is any time since the beginning of the 

recession for which discharge is calculated,

t

o is the time at the beginning of the recession, 

usually set equal to zero,

Qt is spring discharge at time t,

Qo is spring discharge at the start of the recession (to),

and

	 α defines the slope, or recession constant, 

that expresses both the storage and 

transmissivity properties of the aquifer.

By using a semilog plot of discharge and time during a 

spring’s recession curve, one can easily determine a characteristic α value that defines the recession curve slope. For some 

hydrographs, one α value may be obtained that is sufficient to 

describe the slope of the recession curve. It is not uncommon, 

however, for karst springs to exhibit two to three major changes 

in slope on a single hydrograph recession limb, and here it is 

advantageous to evaluate each slope change and its corresponding α value. A common interpretation of these changes is that 

the first and steepest slope represents the transmission of the 

Table 4. Water budget calculations for Orangeville Rise spring, 

southern Indiana (modified from Bassett, 1976). Used with 

permission of the National Speleological Society (www.caves.org).

Interval Duration

(days) I* O* O/I(%) ET* ∆S* Bal.**(%)

June 1 81 26.4 3.8 14 26.4 –2.8 –3.8

August 20, 1972

August 21 70 20.7 2.9 14 20.7 +1.4 –21

October 29

October 30 37 15.3 5.5 36 3.2 +2.3 28

December 5

December 6 44 11.4 10.8 95 2.8 +0.1 –18

January 18

January 19 43 6.6 7.9 120 0.8 –0.4 –26

March 2

March 3 65 32.4 19.7 61 3.7 +1.3 24

May 6

May 7 61 20.1 10.0 50 7.2 –1.6 6

July 5, 1973

*Units are acre-feet × 103.

**Bal. = I – (0 + ET + ∆S), expressed as a percentage of I.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 91

main stormwater runoff pulse through the largest conduits. 

This often is followed by a change to a less steep, intermediate 

recession slope interpreted as marking the beginning of depletion of the stormwater pulse and (or) the spring discharge being 

composed of a mixture of stormwater and stored ground water 

discharging from smaller conduits and larger fractures. The 

final change in slope on the recession curve signals the return to 

base-flow conditions wherein the spring discharge is composed 

of ground-water stores discharging from a network of smaller 

fractures and bedrock matrix.

As noted previously, these differences in spring flow 

characteristics sometimes are referred to as the quick-flow 

(or conduit-dominated) response, the intermediate flow 

response, and the slow-flow (or diffuse-dominated) response.

The α value calculated for a spring discharge recession curve, 

or for each “slice” of a multisloped recession curve, typically 

takes on a characteristic value or range indicative of each 

type of flow regime (table 5). For example, all three karst 

flow regimes (quick-flow or conduit-dominated-flow, mixed 

flow, and slow-flow or diffuse-dominated flow) are evident 

in the discharge hydrograph for San Marcos Springs from the 

Edwards aquifer in Texas (fig. 10).

Basin Hydraulic Properties

Bonacci (1993) and Baedke and Kroethe (2001) have 

suggested that it is possible to estimate the average transmissivity of the karst basin by using spring-discharge hydrograph 

analysis, again following the methods of Rorabaugh (1964) 

and Milanovic ́ (1981a), by applying the equation

T

S

Q

Q L2

y



 ̈

a

© ·

1

 ̧ log

.

1

2

(t 1 071 1

 – t2)

(7)

where

T is aquifer transmissivity,

Sy is specific yield, Q is discharge,

t is time,

and

L is the effective karst basin length.

Results obtained from aquifer (well hydraulic) test analysis may 

be used to estimate the storage (Sy

) parameter, and Shevenell 

(1996) and Teutsch (1992) measured the linear distance from 

the karst spring to the farthest basin drainage divide to obtain 

a value for L. The transmissivity estimate obtained using this 

method needs to be compared to values determined from aquifer 

tests and quantitative dye-tracer tests.

Chemical Hydrograph Separation

Analysis of the flux of dissolved ionic species or isotopes 

in spring discharge during storms provides a useful means of 

identifying water fluxes contributed by different sources of 

recharge and quantifying their proportions in spring discharge. 

Although a variety of naturally occurring isotope and geochemical tracers may be used (Katz and others, 1997; Katz, 

2005), the method requires that there be a distinctive difference in isotope or geochemical composition between water 

discharged at base flow and that discharged during storm-pulse 

Figure 9. Conceptual spring hydrograph showing changes in slope and dominant flow 

regime (conduit, mixed, diffuse) due to differing hydraulic responses (artwork by Earl Greene, 

U.S. Geological Survey).

Diffuse dominated

Mixed

Conduit dominated

Discharge

Time

Conduit Dominated Flow

Mixed Flow

Diffuse Dominated Flow
92 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

events, and(or) between waters contributed from the various 

recharge sources under study, in order to determine mixing 

proportions (Clark and Fritz, 1997). For example, Lakey and 

Krothe (1996) used stable isotopes of oxygen (δ18O) and 

hydrogen (δ2

H) to calculate the mixing proportions of fresh 

meteoric water and stored ground water discharging from the 

Orangeville Rise spring basin in south-central Indiana. Studies 

done by Lee and Krothe (2001) and Trc ́ek and Krothe (2002) 

used sulfate, dissolved inorganic carbon (DIC), δ13C obtained 

from DIC, δ2

H, and δ18O as natural tracers of recharge contributed by matrix ground water, soil water, epikarst water, 

and fresh meteoric water, and developed three- and fourcomponent mixing models of spring discharge by hydrograph 

separation (fig. 11). More recently, Doctor and Alexander 

(2005) used hydrograph recession analysis to identify the flow 

regimes contributing to spring discharge and then grouped the 

sampled chemical and isotopic data according to when they 

were collected with each flow regime. From analysis of these 

data, water chemistry patterns were identified that were distinctive of each hydrograph-defined flow regime (flood flow, 

high flow, moderate flow, and base flow).

Precipitation Response Analysis

In well-developed karst aquifers, large springs will act as 

outlets or drains to the system. The rate of ground-water flow 

and chemical composition of the spring water is directly related 

to the basin-scale hydraulic and transport properties of the karst 

aquifer. Because of the direct connection to surface recharge 

(sinkholes, sinking streams), karst springs have a wide range of 

physical and chemical response to precipitation events. Depending on the degree of conduit-to-fracture/matrix coupling, spring 

hydrographs may show a variable response to recharge events. If 

there is a high degree of conduit-to-fracture/matrix coupling, the 

spring will respond in a relatively short time (hours to weeks) 

to a recharge event, whereas, if this coupling is low, the spring 

response may take many days or weeks. Knowing how the 

spring response is related to the recharge events is so important in karst hydrology that much research has been directed 

toward methods of simulating or predicting this response. 

Three approaches, linear systems analysis, lumped parameter 

(statistical modeling), and numerical deterministic modeling, 

commonly are used to simulate or predict the output function 

(spring discharge) of a karst system on the basis of the known or 

measured input function (precipitation pulse).

Linear Systems Analysis

Linear systems analysis has been used in the hydrological 

sciences for many years to characterize rainfall-runoff relations 

(Dooge, 1973; Neuman and de Marsily, 1976) and has been 

used to describe rainfall (recharge)-spring discharge relations 

in karst systems (Dreiss, 1982; 1983; 1989). The use of a linear 

method to characterize a nonlinear system (karst ground-water 

flow) has been justified on a practical basis. First, it is difficult 

if not impractical to develop a detailed deterministic (numerical) model of ground-water flow in a karst basin because of 

the difficulty in physically modeling fluid movement in pores, 

fractures, and conduits. Secondly, the discharge hydrographs of 

large resurgent springs, like surface-runoff hydrographs, show a 

response that is directly related to recharge provided by rainfall 

events. Linear systems modeling will lump many of the complex processes and is useful for describing the karst aquifer.

If a karst system can be conceptualized to act as a linear, timevariant filter, the relation of continuous input (sinkholes, sinking 

streams, precipitation) can be transformed as continuous output, 

usually spring discharge (Dreiss, 1982) (fig. 12). The convolution 

integral below can be used to describe the relation between the 

output, or spring discharge y(t), and the input, or ground-water 

recharge x(), and h(t-) is the kernel function (Dreiss, 1982),

y( ) (  
 ) ( x ) 
d

d

° t h t d T T T (8)

For two discrete finite series that are causally related, the 

form of the convolution equation above becomes

y t i j x hi-j i N

j=0

i

 $ ¤  012 , , ,..... (9)

Table 5. Characteristic values for the slope of the recession 

curve (α) to determine flow regimes in a karst aquifer.

α1 Prevailing flow regime

0.0018 Slow-flow or diffuse-flow

0.0058, 0.006 Mixed (intermediate) flow

0.25, 0.13, 0.038 Quick-flow or conduit-dominated flow

1

Range of characteristic α's from literature (Baedke and Krothe, 2001; 

Shevenell, 1996; Padilla and others, 1994, Sauter, 1992; and Milanovic ́, 

1981a, b).

Figure 10. Analysis of spring hydrograph of San Marcos Springs in 

Texas identifying the conduit, mixed, and diffuse flow regimes of the 

karst aquifer. (Analysis by Earl Greene, U.S. Geological Survey.)

PRELIMINARY Spring Hydrograph Analysis of San Marcos

Conduit flow A= 0.1

Mixed flow A= 0.03

Diffuse flow A= 0.008

3/10/924/14/935/19/94

6/23/957/27/968/31/97

10/05/9811/09/9912/13/00

DATE

DISCHARGE, IN CUBIC METERS PER SECOND

15

10

5

0
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 93

for N +1 sampling intervals of equal length ∆t, where yi is the 

mean value of the output during the interval i; xj is the mean 

value of the input during the interval j, and hi-j is the kernel 

function during the interval i-j. Thus, if xj and hi-j are known, 

then yi

 can be determined directly by convolution. If xj and yi 

can be identified, then hi-j (kernel function) can be determined 

through deconvolution (Dooge, 1973; Dreiss, 1982, 1989).

Identification of the kernel function from hydrological 

data is difficult because of the nonlinearities in the hydrological system and errors in the measured data. Then the convolution relation becomes:

y t i j x hi-j i N

j=0

i

 $ ¤   Ei 012 , , ,..... (10)

where ∑i are the sum of the residual errors. In this case, the 

identification of the kernel function hi-j is more of an optimization problem and is found by minimizing the sum of the square 

errors. Methods of identifying the kernel functions in karst 

aquifers, in addition to issues involved in defining and working with these functions to predict flow and nonpoint source 

contamination, are presented in Dreiss (1982, 1989) and Wicks 

and Hoke (2000).

Wicks and Hoke (2000) applied and expanded the 

application of linear systems analysis to predict the changes in 

quantity and quality of water from a large karstic basin. Wicks 

and Hoke (2000) were able to predict the first arrival time and 

dispersion of solute discharged from a spring when injected 

into a specific point (fig. 13).

Long and Derickson (1999) applied a linear systems 

analysis approach to the karstic Madison aquifer in the Black 

Hills, South Dakota, to investigate the aquifer’s response 

(head) to an input function. In this instance, stream loss 

(recharge), which was modeled by using a transfer function, 

could be related to the total memory length of the karst system 

(fig. 14). This method could be used as a response-to-recharge 

event-prediction tool in karst aquifers.

Lumped-Parameter Models

In some karst basins, a linear response (kernel function) 

cannot adequately simulate the spring outflow. The purpose 

of lumped-parameter models is to simulate the temporal 

variations in discharge from springs. When the discharge rate 

varies continuously and depends on hydrologic input processes 

of precipitation, sinking streams, evapotranspiration, and 

infiltration, a model can be developed that produces the output 

based on some or all of the inputs (Zhang and Bai, 1996). One 

of the most common nonlinear, lumped-parameter models 

Figure 11. A, Conceptual model of the hydrologic components 

of the upper Lost River drainage basin in south-central Indiana; 

B, Four-component hydrograph separation curves at Orangeville 

Rise (from Lee and Krothe, 2001, reprinted from Chemical Geology, 

copyright 2001, with permission from Elsevier).

Rapid Infiltration

Kernel Function

Storm-Derived Springflow

x

h

y

t–t

t

t

Figure 12. Linear system analysis of a karst conduit spring 

showing the recharge-discharge relation (after Dreiss, 1989).

DISCHARGE, IN CUBIC METERS PER SECOND

3

4

2

1

0

0 30 60 90 120

ELAPSED TIME AFTER STORM EVENT (HOURS)

Total discharge

Phreatic + epikarstic + soil water

Phreatic + epikarstic water

Phreatic water

Orangeville

rise

Epikarstic

discharge

Rain

Epikarst

Deeper diffuse flow

Phreatic

A

B

Epikarst
94 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 14. Calculated and measured head in an observation 

well, analysis is based on an 84-month time period that was used 

to predict a 110-month time period (after Long and Derickson, 

1999). Reprinted from Journal of Hydrology, copyright 1999, with 

permission from Elsevier.

EXPLANATION

Measured head

Calculated head

84 months

110 months

HEAD, IN METERS ABOVE SEA LEVEL

1,090

1,080

1,070

1,060

1,050

1,040

1988 1989 1990 1991 1992 1993 1994 1995 1996

is the Hammerstein Model, and its use is demonstrated by 

Zhang and Bai (1996) and Stoica and Soderstrom (1982). The 

Hammerstein Model is a particularly good, general method for 

developing a lumped-parameter model for a karst basin. The 

model uses a least-squares approach to solve for coefficients 

in the Auto-Regressive Moving Average (ARMA) model and 

then is used to simulate spring discharge.

Zhang and others (1995) developed a lumped-parameter 

model to simulate the temporal variations in discharge from 

Big Spring, Iowa. When precipitation is assumed to be the 

sole input, the simulated spring discharge matched poorly 

with the observed spring discharge. The match improved 

significantly when other variables were added to the model, 

such as evapotranspiration, infiltration, and snowmelt. 

Approaches using lumped-parameter models as demonstrated by these authors can be successfully used to simulate 

spring discharge.

Deterministic (Numerical) Modeling

Numerical modeling has become an important, commonly applied tool for investigating and quantifying many 

complex hydrogeological relations. However, many technical 

and conceptual difficulties remain to be solved to facilitate the 

discretization of conduit geometry or karst basin boundaries, 

parameterization of rapid- and slow-flow karst components, 

and simulation of temporal or spatial changes in saturation and 

flow conditions.

The use of deterministic models is most problematic in 

quick-flow or conduit-dominated karst systems. Data requirements for parameterization and proper model calibration of 

conduit-dominated flow are difficult to meet (Teutsch and 

Sauter, 1991; White, 1999). At present, the technical modeling capabilities and experience base needed to support such 

applications typically are lacking. Conduit-flow modeling codes 

are under development that may be of use in studies where the 

geometry of the conduit system can be fairly accurately mapped 

(Liedl and others, 2003). Some successes in simulating the 

effects of conduit flow have been achieved using a modified 

double-porosity modeling approach (Teutsch and Sauter, 1991) 

and by embedding high transmissivity zones within the grids of 

finite-difference or finite-element models (Worthington, 2003; 

Kuniansky and others, 2001).

Some of the more successful applications of numerical 

modeling have been in the simulation of spring discharge. 

Scanlon and others (2003) evaluated two different equivalent 

porous-media approaches (lumped and distributed parameter) 

to simulate regional ground-water flow to Barton Springs 

in the Edwards aquifer, Texas. Both methods worked fairly 

well to simulate the temporal variability in spring flow 

Figure 13. Predicted and observed (A) discharge at Maramec 

Spring, Missouri; and (B) specific conductance times spring 

discharge water (after Wicks and Hoke, 2000). Reprinted from 

Ground Water with permission from the National Ground Water 

Association, copyright 2000.

Observation

Prediction

Prediction

Observation

–1 0 1 2 3 4 5 6 7 8

–1 0 1 2 3 4 5 6 7 8

250

200

150

100

50

0

400

350

300

250

200

150

TIME (DAYS)

DISCHARGE, IN CUBIC METERS PER SECOND

Q * SpC (m3/s * microS/cm)

TIME (DAYS)

A

B
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 95

(fig. 15). The effect of pumping at a regional scale on spring 

discharge was best simulated by using a lumped-parameter 

distribution approach; however, a detailed evaluation of 

the effect of pumping on water levels and spring discharge 

required a distributed-parameter approach (Scanlon and 

others, 2003). Other successful results have been achieved in 

simulating karst aquifers dominated by slow-flow (diffusedominated) components, or in regional-scale studies where 

the effects of conduit-related heterogeneity can be minimized 

or neglected.

Deterministic rainfall-runoff models have been used 

successfully to estimate ground-water recharge and to simulate 

the hydrologic responses of watersheds in many non-karstic 

terranes (Beven, 2001; Cherkauer, 2004). Their possible 

application to karst hydrology studies seems promising but has 

received little attention thus far. As with deterministic groundwater models, a variety of technical and conceptual difficulties 

currently limit the use of these models. Larger, regional-scale 

modeling may be less problematic (Arikan, 1988). Available rainfall-runoff modeling codes such as TOPMODEL 

(Beven and Kirkby, 1979) and PRMS (Leavesley and others, 

1983) are not well suited to dealing with issues related to 

internal drainage by sinkholes or routing of subsurface flow 

through conduits. Various “workarounds” such as filling and 

smoothing sinkhole depressions, or artificially inflating the 

volume or storage capacities of sinkholes, have been used 

experimentally to achieve model calibration (Campbell and 

others, 2003). These approaches have not been very successful, however, and have resulted mostly in models that do not 

accurately represent the physical hydrogeologic conditions in 

the karst basin or simulate the full range of observed flow conditions and hydrologic responses. Additional research aimed at 

improving the conceptualization and parameterization of karst 

flow systems in rainfall-runoff models is needed and would 

be beneficial.

Water Tracing with Fluorescent Dyes

Water tracing with fluorescent dyes is a particularly useful tool for investigating water fluxes in karst flow systems 

because dye-tracer tests can be used to obtain direct information about flow direction, velocity, and other hydraulic 

characteristics in conduits between specific points of focused 

recharge and discharge. Fluorescent dyes are organic chemicals that absorb light from the ultraviolet part of the spectrum, 

are molecularly energized, and emit light at a longer wavelength range (Käss, 1998). As described by Smart and Laidlaw 

(1977) and Field and others (1995), an ideal water tracer is one 

that (1) is easy to introduce into the aquifer or flow system; 

(2) travels at or near the flow rate of water; (3) is relatively 

conservative—that is, not easily lost through sorption; 

(4) is stable with regard to water chemistry; (5) is easily 

detectable at low concentrations; and (6) has little or no toxicity to humans or aquatic organisms and poses no long-term 

intrinsic threat to the environment. As a group, fluorescent 

dyes possess almost all of these characteristics and, as such, 

they are widely used and popular choices for artificial tracer 

tests in karst studies.

Several of the fluorescent dyes most commonly used 

in water-tracing investigations in karst are listed in table 6. 

The fluorescent characteristics, detection limits in water, and 

sorption tendencies of these dyes are provided in table 7. 

Most of the individual dyes listed are members of a family or 

group of dyes that vary slightly in chemical structure and have 

overall similar fluorescent properties. The xanthene dyes are 

a large group that exhibit fluorescence in the green to orange 

wavelengths of the visible light spectrum (Käss, 1998) and 

includes such well-known tracer dyes as sodium fluorescein 

(also known as uranine), which fluoresces in the green wavelength band (500–570 nanometers [nm]), and Rhodamine WT, 

which fluoresces in the yellow-orange wavelength band 

(570–590 nm). Another large group of tracers is the stilbenes, or optical brighteners—compounds that technically 

are not dyes but are whitening agents—which fluoresce in 

the violet-blue wavelength range of the visible light spectrum 

(380–500 nm). Trade names of individual dyes may vary by 

manufacturer or supplier, so it is advisable to refer to a specific 

tracer dye using the Color Index (CI) generic name and the 

Chemical Abstracts Service (CAS) identification number 

(Field and others, 1995).

Successful use of fluorescent dyes in water-tracing studies 

requires at least a general working knowledge of the physical 

and chemical properties of individual dyes, and the conditions 

and limitations involved in their use. For example, fluorescence 

is pH and temperature sensitive; however, different dyes have 

different ranges of sensitivity and response to these properties. Certain dyes, such as sodium fluorescein, are particularly 

photosensitive, whereas others, such as Rhodamine WT, are not. 

Figure 15. Simulation of Barton Spring discharge in the Edwards 

aquifer, Texas, using a lumped and distributed parameter 

approach (after Scanlon and others, 2003). Reprinted from Journal 

of Hydrology, copyright 2003, with permission from Elsevier.

6

5

4

3

2

1

0

Distributed model

Lumped

model

Measured

1989 1990 1991 1992 1993 19951994 1996 1997 1998

1989 1990 1991 1992 1993 19951994 1996 1997 1998

SPRING DISCHARGE, 

IN CUBIC METERS PER SECOND

RECHARGE, 

IN CUBIC METERS 

PER SECOND

YEAR

15

10

5

0
96 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Table 7. Emission spectra and detection limits for dyes in water (modified from Field, 2002b).

[nm, nanometer; %, percent; μg/L, micrograms per liter]

Dye name

Maximum

excitation λ

(nm)

Maximum

emission1 λ

(nm)

Fluorescence

intensity

(%)

Detection

limit2

(μg/L )

Sorption

tendency

sodium fluorescein 492 513 100 0.002 Very low

eosin 515 535 18 0.01 Low

Rhodamine B 555 582 60 0.006 Strong

Rhodamine WT 558 583 25 0.006 Moderate

Sulpho Rhodamine G 535 555 14 0.005 Moderate

Sulpho Rhodamine B 560 584 30 0.007 Moderate

Tinopal CBS-X 355 435 60 0.01 Moderate

Phorwite BBH Pure 349 439 2 -- --

Diphenyl Brilliant Flavine 7GFF 415 489 -- -- --

Lissamine Flavine FF 422 512 1.6 -- --

pyranine 4603 512 18 -- --

4074 512 6 -- --

amino G acid 359 459 1.0 -- --

sodium napthionate 325 420 18 0.07 Low

1

Approximate values only.

2

Typical values for tracer detection in clean water using spectrofluorometric instrumentation.

3

For pH greater than or equal to 10.

4

For pH less than or equal to 4.5.

Table 6. Some commonly used fluorescent dye types, their dye names, and their respective Color Index and Chemical Abstracts 

Service (CAS) number (from Field, 2002b).

Dye type and common name Color index 

generic name CAS No.

Xanthenes

sodium fluorescein Acid Yellow 73 518-47-8

eosin Acid Red 87 17372-87-1

Rhodamines

Rhodamine B Basic Violet 10 81-88-9

Rhodamine WT Acid Red 388 37299-86-8

Sulpho Rhodamine G Acid Red 50 5873-16-5

Sulpho Rhodamine B Acid Red 52 3520-42-1

Stilbenes

Tinopal CBS-X Fluorescent Brightener 351 54351-85-8

Tinopal 5BM GX Fluorescent Brightener 22 12224-01-0

Phorwite BBH pure Fluorescent Brightener 28 4404-43-7

Diphenyl Brilliant Flavine 7GFF Direct Yellow 96 61725-08-4

Functionalized polycyclic aromatic hydrocarbons

Lissamine Flavine FF Acid Yellow 7 2391-30-2

pyranine Solvent Green 7 6358-69-6

amino G acid -- 86-65-7

In addition, fluorescent dyes have varying ranges of reactivity with geological materials such as clays and other silicate 

minerals (Käss, 1998; Kasnavia and others, 1999). These and 

other important physiochemical characteristics always need 

to be considered prior to use. Useful references include Smart 

and Laidlaw (1977), Mull and others (1988), and Käss (1998). 

Although toxicity generally is not a great concern with most of 

the fluorescent dyes commonly used for water-tracing studies, 

this and other possible environmental concerns are reviewed by 

Smart and Laidlaw (1977) and Field and others (1995).

Dye-Tracer Test Objectives and Design

Dye-tracer testing is a versatile method that can be 

employed in a number of ways by using various combinations 

of field and laboratory techniques that can be tailored to fit 

the specific objectives, context, and scale of the investigation 

(Smart, 2005). The basic goal of any dye-tracer test is to create 

a detectable fluorescent signal in water that can be positively 

identified as originating from the injected tracer dye and that 

can be interpreted in a manner needed to achieve the planned 
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 97

objectives of the test. Careful planning and execution of dyetracer tests is essential so that positive, understandable results 

are obtained from each test—that is, from each injection 

of a tracer dye (Quinlan, 1989). If a dye is injected and not 

detected, the investigator may be faced with difficult and often 

costly decisions that may include whether or not to repeat 

the test, to change the type or amount of dye injected, to use 

additional monitoring sites, to conduct monitoring for a longer 

period of time, or to evaluate the sensitivity of the analytical 

method being used to detect the presence and (or) concentration of the injected dye.

In practice, dye-tracer tests generally are categorized as 

either quantitative or qualitative, depending largely on type of 

monitoring used and the data to be collected and interpreted 

(Jones, 1984a,b; Mull and others, 1988; Smart, 2005). Fully 

quantitative dye-tracer tests require accurate measurement of 

the amount (mass) of tracer dye injected, the discharge from 

the spring or aquifer during the test, and the concentration or 

total mass of tracer dye resurging from the aquifer. Quantitative dye-tracer tests primarily are used to obtain information 

about the time-of-travel and breakthrough characteristics of 

the tracer dye—which are important to contaminant-related 

studies—and to investigate karst conduit structure and flow 

properties (Field and Nash, 1997). Provided that discharge 

is measured simultaneously with tracer concentration at all 

dye-resurgence points, tracer mass recovery can be determined 

and used to make reliable estimates of conduit hydraulic properties including mean residence time, mean flow velocities, 

longitudinal dispersion, and storage (Field, 2002b).

In contrast to quantitative dye-tracer tests, qualitative 

dye-tracer tests are those that require only a determination 

of positive or negative resurgence of injected tracer dye at 

monitoring sites used for the test (Jones, 1984a). Qualitative 

dye-tracer tests are usually conducted to identify flow connections between focused points of recharge and discharge (for 

example, a sinkhole and a spring), thereby helping to delineate 

the trajectories of subsurface flow paths and to estimate an 

approximate maximum time-of-travel (based on the sampling 

interval used). Discharge data typically are not collected, and 

the actual concentrations of dye resurging in water at each 

monitoring site may or may not be determined, depending on 

the analytical methods used. Monitoring for these types of 

tracer tests often is accomplished by using passive detectors 

made of an adsorptive media such as granular activated charcoal to trap the tracer dye.

Planning required for a dye-tracer test typically involves 

a careful review of available hydrogeologic information, selection of dye-injection and dye-monitoring sites, an assessment 

of ambient fluorescence and hydrologic (flow) conditions, and 

selection of a method or methods to be used for dye monitoring and detection that is appropriate for the objectives and 

category of tracer test (that is, quantitative or qualitative). 

Qualitative dye-tracing and quantitative dye-tracing methods 

are not mutually exclusive, and the two methods often are 

used in combination in many karst studies (Quinlan, 1989). 

In common practice, quantitative dye-tracer tests often are 

conducted after subsurface flow routes have been identified 

between specific input points and discharge points by qualitative dye-tracer tests.

During any dye-tracer test, it is important that all potential dye-resurgence sites be identified and monitored to ensure 

that complete recovery of tracer dye is achieved. The results 

of previously conducted dye-tracer tests are very useful in 

the planning of subsequent tests, so every effort needs to be 

made during the planning phase to identify and review existing 

dye-tracer test information. For studies intended to delineate 

subsurface flow paths or karst basin boundaries, previous dyetracer test results, estimates of unit-base flow of local springs, 

and other types of available hydrogeologic mapping data, are 

helpful in establishing the size and boundary of the study area 

required for monitoring. If few subsurface flow routes have 

been dye-traced and karst basin boundaries have been only 

partly delineated, or are not known, it may be necessary to 

monitor many springs in the study area, even those thought 

to be improbable resurgence sites, to ensure detection of the 

injected tracer dye.

Information about local ground-water flow directions 

and hydraulic gradients is extremely useful in the planning 

and the interpretation of dye-tracer tests. Therefore, if suitable 

water-level or potentiometric-surface maps are not available, it is wise to conduct an inventory and synoptic waterlevel survey of wells in the study area prior to initiation of a 

dye-tracer test. For many studies, selected wells need to be 

incorporated in addition to springs and streams as potential 

dye-monitoring sites. A field reconnaissance also needs to be 

done prior to implementation of any dye-tracer test. This is 

often a necessary and underappreciated aspect of the planning 

process. During the reconnaissance, potential dye-injection 

and dye-monitoring sites can be located and inspected to 

identify any logistical issues that may affect the implementation of the planned tracer test. Springs identified on published 

topographic maps often are inaccurately located, and the 

number of spring outlets plotted on a topographic map of a 

given area can be underrepresented as well (Quinlan, 1989). A 

thorough spring inventory needs to be conducted as part of the 

tracer-test planning process by searching existing databases; 

by walking, wading, or boating along surface stream reaches 

within the selected study area; by consulting aerial photographs; and by interviewing local landowners.

Because of the rapid temporal changes in hydraulic 

gradients, flow velocities, and flow directions typical of many 

conduit-dominated karst aquifers, the results obtained during 

a specific dye-tracer test are, strictly speaking, representative 

only of the flow conditions existing at the time of the test. For 

this reason, some consideration needs to be given during the 

planning phase as to whether additional dye-tracer tests need 

to be conducted during specific high- or low-flow conditions. 

For practical reasons, most dye-tracer tests are conducted 

during moderate- or base-flow conditions. During low-flow 
98 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

conditions, greater losses of tracer dye, and longer resurgence 

times, can be expected than at high-flow conditions, because 

of sorption, low-flow velocities, and storage of dye in hydraulic “dead-zones.” Different issues may occur during high- or 

flood-flow conditions. Injected tracer dyes may become too 

diluted and resurge in springs at concentrations below detection limits, the increased turbidity may interfere with dye 

monitoring and detection, physical access to dye-monitoring 

sites may be hindered, and in-situ dye-monitoring equipment 

may be damaged by flooding. In addition, hydraulic damming 

of conduits caused by flooded streams may temporarily halt or 

delay the resurgence of tracer dyes.

Dye Injection

Dyes are typically injected as a “slug” of known weight, 

volume, or mass (fig. 16). A principal cause of negative or 

inconclusive dye-tracer test results is the injection of an insufficient quantity of dye into the aquifer (Quinlan, 1989; Field, 

2003). Proper determination of the amount of dye to inject 

also is needed to ensure that dye resurges at detectable but not 

unacceptably high concentrations, particularly in public or 

private water supplies, and that residual storage of dye in the 

aquifer is minimized. Because of concerns about the possible 

formation of the carcinogen diethylnitrosamine resulting from 

the use of Rhodamine WT dye (Steinheimer and Johnson, 

1986), the USGS adopted a policy that the concentrations 

of Rhodamine WT should not exceed 10 μg/L during tracing tests of surface waters near public water intakes (Water 

Resources Division Memorandum No. 66.90 and 85.82). 

In a review of toxicity and other environmental data, Field 

and others (1995) suggested that the resurgent concentration 

of most commonly used tracer dyes should not exceed 1 to 

2 mg/L (1,000–2,000 μg/L) for more than 24 hours at a point 

of ground-water withdrawal or discharge. These concentration 

limits, while desirable, may not always be possible to achieve 

because of the unpredictability of subsurface flow routes and 

field variables that affect the rate of transport, dispersion, and 

subsequent concentration of dye discharged through conduits.

Historically, a variety of equations have been devised 

to estimate the quantity of dye needed for tracer test injections, based largely on distance to the anticipated resurgence 

point and or estimated ground-water flow velocities. Most of 

these are difficult to apply in practice and do not provide a 

means for the investigator to predict and manage the resurgent 

concentration of tracer dye. These shortcomings are addressed 

in methods devised by Field (2003) and by Worthington and 

Smart (2003).

The Efficient Hydrologic Tracer-Test Design (EHTD) 

method by Field (2003) includes a computer program that 

estimates the amount of dye needed for injection and provides forward modeling capability needed to predict tracerbreakthrough curve characteristics and the time intervals 

needed for effective sampling of the passage of the dye 

pulse—information that is important to planning quantitative 

tracer tests. The EHTD method calculates the amount of dye 

needed for injection by using various forms of the advectiondispersion equation for open-channel flow, closed-conduit 

flow, and flow through porous equivalent media. The program enables the user to designate the mass of tracer dye to 

be injected and an injection flow rate. For open-channel and 

closed-conduit flow conditions, the EHTD method requires the 

following input values: (1) discharge at the sampling station 

(spring), (2) estimated longitudinal distance from the dyeinjection site to the anticipated resurgence site, (3) estimated 

cross-sectional area of the discharge point (that is, spring or 

stream cross-sectional area), and (4) a sinuosity factor applied 

to straight-line estimates of the distance between a dye injection and potential dye resurgence site.

The method proposed by Worthington and Smart (2003) 

relies upon the empirically derived equations:

M = 19 (LQC)

0.95 (11)

and

M = 0.73 (TQC)

0.97 (12)

where

M is mass of tracer dye injected (grams/meter3),

L is anticipated distance between the injection 

site and the anticipated primary resurgence 

site (meters),

Q is discharge at the anticipated resurgence 

(meters3/second),

C is peak tracer concentration at the anticipated 

resurgence (grams/meter3),

and

T is traveltime as determined from prior tracingtest results (seconds).

Using either equation, the investigator can select a target concentration desired for resurging tracer dye and solve to determine the required amount (mass) of dye needed for injection.

In practice, dye injection is best accomplished at locations that provide rapid, direct transport of the tracer into 

conduits, thus minimizing loss of dye through photochemical decay, sorption, or other field conditions. Open-throated 

swallets in sinkholes and the swallow holes of sinking streams 

are ideal sites. In the absence of naturally occurring runoff 

(inflow), dyes can be injected into a stream of potable water 

discharged from a tanker truck or large carboy. In general, 

300 to 500 gallons of water are a minimum quantity needed 

for dye injection, and quantities of 1,000 gallons or more 

are preferable. Approximately one-half of the water is used 

to initiate flow into the swallet prior to dye injection. This is 

done to test the swallet’s drainage capacity, to initiate flow, 

and to flush the flow path to minimize losses to sorption. The 

remainder of the water is discharged after the dye is injected 

as a “chaser.” Under most conditions, this technique does not 

substantially change the naturally occurring flow conditions 

or alter hydraulic heads in the aquifer.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 99

Several practical tips regarding dye injection that may 

be useful to consider during the planning of dye-tracer tests 

include the following:

•	 Open-borehole wells or screened wells can be used as 

dye injection sites. Although a pre-flush is not necessary prior to injecting the dye, it is advisable to conduct 

a falling-head slug test in order to test the hydraulic 

connection with the aquifer and to estimate the local 

hydraulic conductivity and rate of discharge of tracer 

from the well. After injecting dye, it is necessary to flush 

the dye from the well using several borehole volumes of 

potable water. It is important to control the volume and 

rate of water inflow during the flush to prevent the well 

from overflowing with dye-laden water.

•	 In locations where available sinkholes do not contain 

open swallets, dye injection may be accomplished 

by drilling a temporary injection well. Ideally, these 

injection wells would be drilled to intercept fractures or 

solutional openings in the bedrock; however, successful 

injection into the epikarst may be accomplished by completing the well at the top of the karstic bedrock. Aley 

(1997) discusses in detail the issues involved in conducting dye-tracer tests through the epikarst zone.

•	 Dye injections also can be made through the epikarst 

by excavating a pit into the soil; however, dye losses 

may be significant, and the quantity of dye used for the 

injection usually must be increased several times above 

the “normal” dosage amount.

•	 The injection of dye into flooded sinkhole depressions or 

swallets choked with sediment generally is not advisable, particularly for quantitative tracer tests. Unless 

there is evidence that drainage through the regolith into 

the subsurface is relatively rapid, excessive loss of the 

tracer dye may be incurred. If necessary, swallets that 

are partly choked with sediment may be cleared out with 

a shovel or backhoe and pre-tested for drainage capacity 

prior to an attempted injection of dye.

Figure 16. Dye injections: A, sodium fluorescein injection into collapse sinkhole formed in a pond (stream of water is outflow from a 

settling pond at a public supply water-treatment plant); B, Rhodamine WT injected into sinking stream; C, injection of Rhodamine WT into 

a water-level observation well (photographs by Charles J. Taylor, U.S. Geological Survey).

B

A

C
100 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

•	 A slug injection may not be an effective means of 

attempting to trace flow from a losing stream—that 

is, into a stream not fully diverted underground by 

swallow holes—because too much of the dye may be 

flushed downstream before it infiltrates the subsurface. 

Under such conditions, dye injection may be more 

effectively accomplished by using the continuousinjection technique described by Kilpatrick and Cobb 

(1984). A recent paper by Field (2006) specifically 

examines the problem of conducting dye-tracer tests 

from losing streams.

Dye Monitoring and Detection

As dictated by the tracer-test objectives and the resources 

available, a variety of methods can be used to monitor for and 

detect the resurgence of injected tracer dyes, including direct 

visual observation, fluorometric analysis of discrete water 

samples or eluant obtained from granular activated charcoal 

detectors, and in-situ continuous-flow fluorometry. Dyes often 

can be visually detected in water at parts-per-million concentrations, whereas some method of fluorometric analysis is 

needed to detect dyes at subvisual concentrations. Three types 

of fluorometers are commercially available: scanning spectrofluorophotometers, filter fluorometers, and in-situ submersible 

fluorometers. Each of these instruments operates essentially 

by selectively measuring the fluorescent intensity of a sample 

(for example, water) that has been selectively excited (Duley, 

1986). The selective range of light wavelengths used to excite 

the sample is called the excitation spectrum, and the selective 

range of light wavelengths that are measured by the fluorescent 

intensity is called the emission spectrum (Käss, 1998). Depending on which type of the three instruments is used, common 

tracer dyes can be detected in water at concentrations as low as 

parts per trillion—although environmental factors usually limit 

unequivocal detection to the range of parts per billion or greater 

(Smart and others, 1998).

Scanning spectrofluorophotometers are research-grade 

laboratory instruments that use a system of monochromators, diffraction gratings, and bandwidth slits to scan across 

user-selected excitation and(or) emission spectra at selected 

bandwidth intervals. These instruments are exceptionally 

sensitive—dyes often can be detected in the parts-per-trillion 

range—and enable precise characterization of the various sources of fluorescence in a sample. One advantage of 

these instruments is that they can be used to do synchronous 

scanning, a technique in which the excitation and emission 

monochromators are scanned together at a fixed wavelength 

difference determined by the separation (in nanometers) 

between the excitation and emission peaks for the dye(s) of 

interest (Duley, 1986; Rendell, 1987). For most xanthene dyes, 

this distance is approximately 20 to 25 nanometers (Käss, 

1998). The synchronous scanning technique is useful for analyzing unknown mixtures of fluorescent solutes having various 

excitation wavelengths because it provides a spectral “fingerprint” for each solute present and therefore can be used to 

identify the presence of multiple tracer dyes in a single sample 

(Käss, 1998) (fig. 17). The tradeoff in using these instruments 

is that they require a good working knowledge of relatively 

specialized fluorescence spectroscopy methods and the use of 

rigorous quality-control methods, which can be quite time and 

labor intensive.

Filter fluorometers, such as the Turner Designs Model 11, 

are versatile instruments that can be set up to work under field 

or laboratory conditions, to analyze discrete samples of water 

or eluant or be used with flow-through cells and pumps to 

continuously monitor the change in fluorescence due to the 

passage of a dye pulse in water. These instruments have userexchangeable glass filter kits that transmit light in the excitation and emission wavelengths of fluorescein or rhodamine 

dyes and are capable of identifying dyes at concentrations in 

the parts-per-billion range. Because the excitation and emission wavelengths are fixed by the set of filters installed, only 

one tracer dye at a time can be identified in a sample. Filter 

fluorometers are dependable “workhorse” instruments widely 

used for dye-tracer studies in karst. As discussed by Smart 

and others (1998), however, there are a number of practical 

constraints on the use of filter fluorometers, the most serious 

of which is that the sensitivity of these instruments may be 

adversely affected by ambient fluorescence so that it is possible to obtain apparently significant fluorescent readings—

indicating positive detection of dye—with a particular filter 

set when the dye of interest is not actually present. Such false 

positive readings result from the presence of other fluorescent 

solutes having fluorescence spectral properties that overlap 

those of the tracer dye of interest (Smart and others, 1998).

Recently, manufacturers such as Turner Designs and 

Yellow Springs Instruments have introduced submersible fluorometers that can be used for in-situ continuous-flow monitoring of either sodium fluorescein or Rhodamine WT dyes. The 

filters needed for detection of each dye are preinstalled by the 

manufacturer in an optical probe assembly. These instruments 

include internal data loggers capable of recording thousands 

of data values in nonvolatile flash memory and simultaneously 

collect temperature and turbidity data as needed to correct 

the recorded fluorescent intensity values. Continuous-flow 

fluorometry conducted with either filter fluorometers or 

submersible fluorometers provides significant advantages 

for quantitative dye-tracer tests because highly resolved dyebreakthrough curves can be obtained whose properties are 

not as affected by sampling biases or by insufficient sampling 

frequency (Smart, 1998). Quality control also may be considerably improved because the water is analyzed directly without excessive sampling and handling activities that potentially 

increase the chances of sample contamination or degradation. 

These advantages sufficiently outweigh any potential loss of 

spectral precision (Smart and others, 1998).

For quantitative analysis, all fluorometers must be calibrated so that the concentration of dye is determined by the 

fluorescent intensity of the sample measured relative to that of 

dye-concentration standards. Standards are prepared from the 

tracer-dye stock solution by using gravimetric and serial dilution 
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 101

techniques in the manner described by Wilson and others (1986) 

or Mull and others (1988). Turner Designs offers a number of 

application notes that can be downloaded or ordered from their 

Internet website (http://www.turnerdesigns.com) that describe 

in detail the procedures involved in the preparation of dye 

standards and the calibration of filter fluorometers. The preparation of dye-concentration standards is a critical procedure and 

needs to be undertaken with great care. Errors introduced into 

the standards preparation process will adversely affect instrument calibration and, for quantitative tracer tests, may result 

in serious mass-balance errors (Field, 1999b). Adjustments to 

account for the percent actual tracer in powdered and liquid 

dyes, and also for specific gravity in liquid dyes (Field, 1999b, 

2002b) (table 8) must be factored in during the calculation of 

dye standard concentrations. Dye-concentration calibration 

curves typically are made by using a logarithmic distribution of 

dye-concentration standards ranging over two or three orders of 

magnitude (Alexander, 2002).

In practice, error in dye detection and(or) determining 

dye concentration in water is dominated by issues of ambient (background) fluorescence, loss of tracer (that is, due 

to adsorption or photodegradation), and improper sampling 

frequency (Smart, 2005). Ambient (background) fluorescence 

is probably the largest single source of systematic error in dye 

Figure 17. Dye spectral “fingerprints” obtained from use of the synchronous scanning method: A, no 

fluorescent tracer dye is present; B, sodium fluorescein (or uranine) tracer dye is present; C, Rhodamine WT 

tracer dye is present; D, sodium fluoresein and Rhodamine WT tracer dyes are present (after Vandike, 1992).

100

RELATIVE FLUORESCENCE 50

0

492 542 592

EMISSION WAVELENGTH (NANOMETERS)

POSITIVE—FLUORESCEIN (OR URANINE)

100

50

0

492 542 592

EMISSION WAVELENGTH (NANOMETERS)

POSITIVE—FLUORESCEIN AND RHODAMINE WT

RELATIVE FLUORESCENCE

100

50

0

492 542 592

EMISSION WAVELENGTH (NANOMETERS)

POSITIVE—RHODAMINE WT

RELATIVE FLUORESCENCE

100

50

0

492 542 592

EMISSION WAVELENGTH (NANOMETERS)

NEGATIVE (NO DYES PRESENT)

RELATIVE FLUORESCENCE

A

B

C

D
102 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

tracing and must be carefully assessed prior to initiation of any 

(qualitative or quantitative) dye-tracer test. For quantitative 

tests, ambient background levels occurring in the range of the 

emission peak of the tracer dye being used must be subtracted 

to accurately calculate dye concentrations. Often, the choice 

of dye selected for a particular tracer test is influenced by the 

presence and level of fluorescent intensity of ambient fluorescent interferences. Potential sources of interference with 

tracer dyes include naturally occurring humic and fulvic acids, 

certain species of algae, petroleum hydrocarbons, optical 

brighteners discharged in septic or treated waste-water effluent, automotive antifreeze chemicals (a widespread source of 

fluorescein), and hundreds of other dyes and organic chemicals used in industrial, commercial, and household products 

(Käss, 1998). In general, ambient background interferences 

typically are more problematic for optical brighteners and 

for xanthene dyes that fluoresce in the blue-green spectral 

wavelengths (Käss, 1998), and less problematic for xanthene 

dyes that fluoresce in the yellow-orange spectral wavelengths 

(Smart and Karunaratne, 2002).

One important point to consider is that the timing, 

duration, and intensity of fluorescence can vary considerably, 

depending on its sources, during the period over which ambient fluorescence is being monitored (Smart and Karunaratne, 

2002). For this reason, it is advisable to conduct background 

monitoring for a period of at least several days or weeks 

immediately prior to initiating any dye-tracer test. It is also 

advisable to contact local, state, and Federal water-resources 

agencies at this time to determine whether or not other tracer 

tests are in progress or have recently been completed in order 

to be aware of, and avoid, interference and potential cross 

contamination with a previously injected tracer dye.

Because of ambient fluorescence and other analytical 

variables involved in fluorometry, there may be some subjectivity and difficulty in assessing the results of a single sample 

analysis—that is, the question might be asked “Is there enough 

of a change in fluorescent intensity to indicate that the tracer 

dye has been detected?” These decisions are made somewhat more objectively if minimum threshold concentrations 

or fluorescent intensity values are established by statistical 

methods or some other means to ensure that the fluorescence 

intensity or concentration measured in a sample is sufficiently 

higher than background to provide a high confidence level that 

dye was positively detected. From the literature, it appears 

that many researchers apply an arbitrary 10:1 signal-to-noise 

ratio for fluorescent intensity or dye concentration measured 

at the expected emission peak of the tracer dye as a minimal threshold for reporting the positive detection of dye in a 

sample (Smart and Simpson, 2001). A number of analytical 

and data post-processing techniques also have been devised in 

an attempt to enhance the detection of tracer dyes, particularly 

when working under “noisy” fluorescent background conditions (Smart and others, 1998; Smart and Smart, 1991; Lane 

and Smart, 1999; Tucker and Crawford, 1999). More recently, 

the use of advanced spectral analysis techniques has been 

explored as a means of better distinguishing tracer dyes from 

ambient background fluorescence (Alexander, 2005).

In general, caution needs to be used when making a 

determination that breakthrough and detection of an injected 

tracer dye has occurred based on only one “positive” sampling 

result. Evidence of dye breakthrough and detection is more 

conclusive if repeated positive detections are obtained, particularly where these results demonstrate a change in dye concentrations or fluorescent intensity that is indicative of the passage 

of a dye pulse and subsequent return to ambient fluorescent 

conditions. This is a principal reason that some researchers strongly recommend the use of quantitative dye-tracer 

tests methods, which include high-frequency sampling using 

automatic water-samplers or continuous-flow fluorometry, 

whenever possible (Field, 2002b; Kincaid and others, 2005). 

The passage of a dye pulse, however, also can be conclusively 

demonstrated by changes in fluorescent intensity or equivalent 

dye concentration obtained during qualitative dye-tracer tests 

using passive samplers, provided that a sufficiently high sampling frequency is used. Where questionable or inconclusive 

dye-tracer test results are obtained, it is advisable to review 

the tracer test design—particularly the methods used for 

monitoring and detection—and repeat the test using a different 

tracer dye.

Use of Charcoal Detectors

As previously indicated, the use of passive detectors 

containing granular activated charcoal is a popular method of 

monitoring for dye resurgence during qualitative tracer tests. 

The detectors typically are constructed of fiberglass screen, 

nylon netting, or a similar material, fashioned into packets 

that contain several grams of charcoal sampling media. The 

Table 8. Percent active tracer, and specific gravity, measured 

for some commonly used fluorescent dye tracers. These may vary 

from batch to batch and should be determined for the specific lot 

of dye being used for mass-balance calculations attempted during 

quantitative dye-tracing tests (Field, 2002b).

Color index

generic name

Powder 

dye 

(%)

Liquid 

dye 

(%)

Specific 

gravity 

(g cm–3)

Acid Blue 9 74.0* 37.0 --

Acid Red 52 90–90.2 18.0 1.175

Acid Red 87 86.0 26.0 --

Acid Red 388 85.0** 17.0 1.160

Acid Yellow 73 60.0 30.0 1.190

Basic Violet 10 90.0 45.0† --

Fluorescent Brightener 351 60.0 -- --

Values listed are equal to within 5.0 percent.

*

Acid Blue also is sold with a Food, Drug and Cosmetic (FD&C) purity 

equal to 92.0%.

**Acid Red 388 is not commercially available in powder form.

†

Basic Violet 10 as a liquid is mixed with glacial acetic acid.

Note: The values listed are specific to one manufacturer; crude dye stocks 

can and will vary significantly with manufacturer.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 103

size and shape of the packets and the amount of charcoal used 

in them is not particularly critical—the only requirements 

are that detectors be relatively durable, securely retain the 

activated granular charcoal, and allow water to flow easily and 

evenly through the packets. The detectors, or “bugs”, generally are used in rapidly flowing water in streams and springs 

suspended above the substrate using a wire-and-concrete or 

wire-and-brick anchor. The detectors also can be staked or 

pinned directly into the streambed in very shallow water, and 

they can be easily suspended in monitoring or water-supply 

wells using, for example, monofilament line, snap-swivels, 

and steel shot-weights sold as fishing tackle. A common 

practice is to use detectors at all anticipated resurgences and 

exchange the detectors at 2 to 10 day intervals throughout the 

duration of the test (Quinlan, 1989). As a practical matter, it is 

generally inadvisable to leave detectors in the field longer than 

10 days because of physical degradation that can diminish the 

adsorptive capability of the charcoal.

The principal advantage of using charcoal detectors 

is their economy and relative ease of use for ground-water 

reconnaissance studies, for simultaneous monitoring of many 

potential dye resurgence sites, and for mapping of conduitflow paths or karst basin boundaries in areas where these are 

primarily or completely unknown. The detectors are relatively 

easy to conceal, thus minimizing the potential for disturbance and vandalism; and they are inexpensive, most of the 

cost being associated with their use onsite, collection, and 

analysis (Smart and Simpson, 2001). Handling, storage, and 

transportation requirements used in the exchange of detectors are not particularly critical with the exception of simple 

procedures needed to eliminate the potential for misidentification of detectors or cross contamination during handling and 

to prevent degradation of the dyes adsorbed by the charcoal 

(Jones, 1984a).

Another benefit of using charcoal detectors is their ability 

to concentrate dye at levels 100 to 400 times greater than the 

concentration of dye resurging in water, thereby helping to 

increase the probability of a positive detection of dye at distant 

monitoring sites (Smart and Simpson, 2001, 2002). To expel 

adsorbed dye, a few grams of charcoal are removed from a 

detector packet and eluted in an alkaline-alcohol solution. Two 

popular eluants include the so-called “Smart solution” (Smart, 

1972), prepared by mixing 1-propanol, distilled water, and 

28 to 30 percent ammonium hydroxide in a 5:3:2 ratio, and a 

solution of 70 percent 2-propanol and 30 percent deionized 

water saturated with sodium hydroxide (Alexander, 2002). 

Upon mixing, the solution separates into a lighter (saturated) 

and denser (supersaturated) liquid and it is the lighter phase 

that is decanted off and used as the actual eluant. Other eluant 

formulas may be chosen to enhance the elution of specific 

tracer dyes (Käss, 1998). Any prepared eluant always needs 

to be scanned as a blank before actual use (Alexander, 2002). 

Generally, 1 hour of elution is needed before fluorometric 

analysis can be done, although different dyes have different 

optimal elution times in various eluants (Smart and Simpson, 

2001). Elution may be done with wet or dry charcoal; for 

longer term storage, however, charcoal samples need to be 

completely dried to prevent microbial degradation of the 

adsorbed dye.

If dye elutes from the charcoal below visible concentrations, an aliquot of the eluant can be removed for analysis 

by using either a filter fluorometer or a scanning spectrofluorophotometer (Smart and Simpson, 2002). As with water 

samples, the relative concentration of tracer dye in the eluant 

is determined by the fluorescent intensity, or the area of the 

spectral peak, measured at the emission wavelength of the dye 

(Jones, 1984b; Smart and Simpson, 2002). Because fluorescence for most tracer dyes is pH-dependent, the emission 

wavelengths for dyes in alkaline-alcohol eluants generally are 

shifted several nanometers relative to the emission wavelengths reported for dyes in water samples at or near neutral 

pH (Käss, 1998), and the emission peak characteristics and 

calibration curves obtained by fluorometric analysis may vary 

for different eluant formulations.

Although the use of charcoal detectors is relatively easy 

and has many potential benefits, the method is not without its 

shortcomings. Variables in the field, differences in the adsorptive efficiency of charcoal with various tracer dyes, complexities associated with the adsorption-desorption process of 

organic solutes on charcoal, and other variables introduced as 

a result of processing in the laboratory, preclude any determination of the actual concentrations of tracer that resurged in 

water and the replication of analytical results obtained from 

eluted charcoal (Smart and Simpson, 2001, 2002). The amount 

of dye concentrated on the detectors is a factor of the rate 

of flow through the detectors, the total surface area exposed 

to the dye, and of the length of time of the exposure. Dye 

concentrations measured in eluant also are affected by the time 

and method of elution (Smart and Simpson, 2001), therefore 

the concentrations of dye measured in eluant have a nonlinear, 

nonquantifiable relation to the concentrations of dye resurging 

in water. It is primarily because of these difficulties that some 

researchers, such as Field (2002b), have expressed reservations 

about the use of charcoal and strongly advocate the collection 

and quantitative analysis of water samples, or use of in-situ 

continuous-flow fluorometery during dye-tracer tests. Assuming that a qualitative tracer test design will meet the objectives 

for the study, many of these difficulties can be overcome by 

careful evaluation of ambient fluorescence, careful tracertest design, proper application of analytical methods, and the 

application of rigorous QA/QC techniques during all field and 

laboratory activities. All of these issues deserve careful consideration during the planning phases of a dye-tracer test.

Proper evaluation of ambient fluorescence (background) 

is even more critical with activated charcoal than with water 

samples. When used in the field, activated charcoal captures 

a broad range of organic molecules, and a complex hierarchy 

of adsorption occurs based on the range of adsorptive sites, 

their accessibility, and the loading (composition and duration 

of flow) (Smart and Simpson, 2001). As with tracer dyes, 

these solutes will be recovered on the charcoal at substantially 

higher levels than the concentrations present in the water. 
104 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

During spectrofluorometric analysis, the fluorescent signatures 

created by these solutes may be confused with, or mask, dye 

spectral peaks (Smart and others, 1998). High levels of organic 

solutes can foul the detectors because the solutes can consume 

the available adsorptive capacity of the carbon. Older charcoal 

tends to be less adsorptive than fresh charcoal, because of 

denaturing of the more energetic adsorption sites and capture 

of organic molecules from the surrounding atmosphere (Smart 

and Simpson, 2001, 2002).

Unfortunately, there is no ready means of distinguishing 

a genuine tracer recovery from accidental contamination of the 

charcoal detector (Smart and others, 1998). Wood charcoals, 

including coconut shell used to manufacture granular activated 

charcoal, can contain 10 to 20 percent fluorescein-type functional groups, which may create apparent false-positive peaks 

for sodium fluorescein dye when eluted (Alexander, 2002); 

however, this problem is usually manageable in that the compounds generally have a weak fluorescent intensity and seem 

to be flushed from charcoal by 1 to 2 days exposure to flowing 

water (Smart and Simpson, 2001).

Dye-Breakthrough Curve Analysis

Analysis of dye-breakthrough curves (measured dye concentration over time) obtained via quantitative dye-tracer tests 

is an effective means of determining conduit-flow characteristics in karst aquifers (Smoot and others, 1987). Advantages 

provided by using this method, listed by Kincaid and others 

(2005), include:

•	 Plotting of the increase and decrease in fluorescence 

increases the confidence that tracer-test results are 

accurate and reflect the actual passage of the injected 

tracer dye through the aquifer.

•	 More accurate estimates of flow velocity can be calculated using time-to-peak concentrations.

•	 Integrating the area under the dye-breakthrough curve 

allows for estimation of the mass of tracer recovered at a 

sampling site and, therefore, the relative contribution of 

flow from the injection site to the tracer resurgence site.

•	 If it can be assumed that 100 percent of the tracer dye 

was recovered, evaluation of the shape of the dyebreakthrough curve provides data needed for estimation of hydraulic properties such as longitudinal dispersion, Reynolds and Peclet numbers, and discharge.

Important characteristics of the dye-breakthrough curve 

(fig. 18) include the first arrival or time to the leading edge of 

the dye pulse, time to peak concentration, elapsed time of passage of the dye pulse, and time to trailing edge or passage of 

the dye pulse. As Field (1999a) notes, these characteristics are 

not entirely objectively defined because they are dependent on 

sampling frequency and instrument sensitivity. Apart from sampling frequency bias, the shape and magnitude of the dye-breakthrough curve are most influenced by: (1) the amount of dye 

injected, (2) the velocity and magnitude of the flow, (3) internal 

structure and hydraulic properties of the conduit flow path taken 

by the tracer dye, and (4) other factors that affect mixing and 

dispersion of the tracer dye in the aquifer (Smart, 1998; Field, 

1999a). Thus, the dye-breakthrough results obtained represent 

the transport characteristics of the tracer dye under the hydrologic conditions occurring during a particular test. Repeated 

quantitative tracer tests may be needed to characterize tracer 

dye characteristics under different flow conditions. Normalized 

dye-concentration and dye-load curves are used to compare 

and evaluate the transport characteristics of dye under different 

hydrologic conditions (Mull and others, 1988).

The physical properties of the dye-breakthrough curve 

provide information about conduit structure and organization 

(Smart, 1998). The dispersion of a dye plume increases with 

time and distance, and the pattern of dye recovery obtained 

reflects the effects of processes such as dilution, longitudinal 

dispersion, divergence, convergence, and storage, which are 

related to discharge and conduit geometry. The effects of longitudinal dispersion of the dye pulse usually are seen as a lengthening of the breakthrough curve (“tailing”), and the effects of 

tracer retardation usually are seen as multiple secondary peaks 

in dye concentration along the profile of the breakthrough curve. 

Interpretation of complex or multipeaked dye-breakthrough 

curves may be difficult because the factors contributing to tracer 

dispersion or retardation may include anastomosing (bifurcation or braiding) conduit-flow paths; flow reversal in eddies and 

variability in conduit cross-sectional areas (Hauns and others, 

2001); intermittent storage and flushing of hydraulically stagnant zones (Smart, 1998); and interconnected zones of higher 

and lower fracture permeabilities (Shapiro, 2001). The potential effects of such factors on the shapes of dye-breakthrough 

curves under high-flow and low-flow conditions are illustrated 

in figure 19. Interpretation of the physical characteristics of the 

breakthrough curves usually cannot be based solely on the pattern of recovery of dye, but also on knowledge of the physical 

hydrogeology and conduit structure in the karst aquifer under 

study (fig. 20) (Jones, 1984b).

A variety of hydraulic properties, including the hydraulic 

radius or (assuming open-channel flow conditions) hydraulic 

depth, Peclet number, Reynolds number, Froude number, and 

hydraulic head loss can be estimated using dye-breakthrough 

curve data if it can be assumed that nearly 100 percent of the 

tracer dye was recovered (Field, 1999a; Mull and others, 1988; 

Field, 2002b). The computer program QTRACER2 (Field, 

2002b), automates curve plotting and facilitates many of the 

calculations involved in the dye-breakthrough curve analysis 

obtained by analysis of dye-breakthrough curve data.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 105

Figure 18. Some important physical characteristics of a dye-breakthrough curve (from Mull 

and others, 1988).

6

5

4

3

2

1

0

0 2 4 6 8 10 12

TIME FROM INJECTION, IN HOURS

MEASURED DYE CONCENTRATION,

IN MICROGRAMS PER LITER

Injection of dye (t0) Time to trailing edge (tT

)

Travel time of centroid of dye

mass, or mean travel time (t)

Persistence, period of time a

given concentration is equaled

or exceeded

Time to peak dye concentration

(tpeak)

Elapsed time for dye passage

Time to leading edge (tL)

Figure 19. Example of dye-breakthrough curves for two dye-tracing tests conducted 

in the Edwards aquifer, Texas, showing a quick-flow response with little or no dispersion 

(Injection site A, left), and a slow-flow response showing the effects of dye dispersion 

(Injection site B, right) (courtesy of Geary Schindel, Edwards Aquifer Authority).

0

0.05

0.1

0.15

0.2

0.25

Fri 0:00 Fri 12:00 Sat 0:00 Sat 12:00 Sun 0:00 Sun 12:00 Mon 0:00 Mon 12:00 Tue 0:00 Tue 12:00 Wed 0:00

PARTS PER BILLION

Time of 

dye injections

Injection site B—Slower flow, 

 significant dye dispersion due 

 to multiple flow paths and(or) 

 hydraulically stagnant zones

Injection Site A—Rapid open 

 channel or pipe flow, little 

 dye dispersion

Eosine (511)

Fluorescein (491)

EXPLANATION
106 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Figure 20. Shapes of hypothetical dye-breakthrough curves affected by changes in hydrologic conditions 

(high flow, low flow) and conduit geometry (modified from Jones, 1984b, after Smart and Ford, 1982). Used with 

permission from the National Speleological Society (www.caves.org).

Mean Tracer-Dye Residence Time

Mean tracer-dye residence time is the length of time 

required for the centroid (gravity mass) of the tracer dye to traverse the entire length of the karst basin, thus representing the 

average time of flow through the basin. The centroid generally 

is not the same as the peak concentration of the tracer-dye 

mass in the tracer-breakthrough curve, but the more the dye 

plume conforms to Fick’s law (the mass of the diffusing 

substance passing through a given cross section per unit time 

is proportional to the concentration gradient) the less obvious 

the difference between the dye centroid and peak concentration will be.

Mean tracer-dye residence time is estimated by the 

equation:

t tC t Q t dt C t Q t dt m 

d d

°° () () / ( ) ( )

0 0

, (13)

where

t is time of sample collection,

C(t) is measured dye concentration of the sample,

and

Q(t) is the discharge measured at the sampling 

location.

Tracer-dye residence time will vary from nearly zero for 

instantaneous transport to almost infinity where the tracer 

mass is mostly lost to dispersion or storage in the aquifer. 

If QTRACER2 or another suitable mathematical software 

program is not used, and the sampling frequency was done at 

regularly spaced intervals, the integration can be done by using 

a simple summation algorithm as detailed in Field (2002b) and 

by Mull and others (1988).

Mean Dye Velocity

Mean tracer velocity (of the dye mass centroid) represents the average rate of travel of dye through the karst basin 

and is estimated by:

V x tCtQ t dt C t Q t dt ( ) M  ( . / ) () () / ( ) ( )

d d

° ° 1 5

0 0

, (14)

where

x is straight-line distance between the dye 

injection and resurgence site,

and

1.5 is a constant representing the conduit 

sinuosity factor (Field, 1999a).

Dye

injection

Springs

Conduits

2

1

2

1

1

Spring 1

Spring 2

TIME

TIME

TIME

TIME

CONCENTRATION

TIME

CONCENTRATION

TIME

CONCENTRATION

TIME

CONCENTRATION

TIME

CONCENTRATION

CONCENTRATION CONCENTRATION CONCENTRATION

Spring 2

Spring 1

Spring 2

1

2

1

2

DILUTION

HIGH FLOW CONDITIONS LOW FLOW CONDITIONS

DISTRIBUTION

STORAGE

ANASTOMOSING

CHANNELS
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 107

Tracer Mass Recovery

The accuracy of calculations of mean tracer-dye residence time, flow velocities, and other conduit hydraulic 

properties from dye-breakthrough curve data is entirely 

dependent on tracer mass recovery. Few tracing tests result 

in 100 percent recovery of dye, but as the percentage of mass 

recovery decreases, the margin of error in the calculated 

hydraulic parameters increases and confidence in the values 

obtained declines. Tracer recovery may be affected by the 

internal structure of conduit networks (Brown and Ford, 1971; 

Atkinson and others, 1973). It therefore is important to assess 

tracer mass recovery as a starting point in the analysis of quantitative dye-tracing tests.

The quality of the tracer experiment may be quantified in 

terms of the relation between the mass of dye tracer injected 

(Min ) during the experiment and the total mass of dye tracer 

recovered (Mr

). A test accuracy index proposed by Sukhodolov 

and others (1997) is calculated by:

AI = Min – Mr/Min (15)

This index provides a semiquantitative assessment of the 

quality of the test. A value AI

 = 0 indicates a perfect tracing experiment with no loss of tracer dye mass. A positive 

AI

 value indicates that more tracer dye mass was injected 

than was recovered—a common result, whereas a negative 

value indicates more dye mass was recovered than was 

injected—an impossibility unless residual tracer dye is present 

in the aquifer, errors are made in determining the dye concentration in test samples, or initial calculations of the injected 

dye mass are in error.

In the previous equation, the value for Mr

, the total mass 

of tracer dye recovered is given by the equation:

M C(t)Q(t)dt r 

d

°

0

. (16)

A simple summation algorithm can be used to facilitate the 

calculations needed to obtain the value for Mr

 as described by 

Field (2002b):

Mr  C t Q t dt z

d

° ( ) ( )

0

, (17)

C i Q i ti

i

n

() ()$ z 

¤1

, (18)

and

t c ( ) C Qi i

i

n



¤1

, (19)

where

t

c is a time conversion needed to obtain units of 

mass only.

The previous equations assume that the total dye mass is 

recovered at a single spring site. If dye has resurged at multiple spring outlets, these calculations are repeated for each 

site and the results are summed to obtain Mr

.

Summary

The hydrogeologic complexities presented by karst terranes 

often magnify the difficulties involved in identifying and measuring or estimating water fluxes. Conventional hydrogeologic 

methods such as aquifer tests and potentiometric mapping, though 

useful, are not completely effective in identifying the processes 

involved in the transfer of water fluxes in karst, or in characterizing the hydrogeologic framework in which they occur, and may 

provide erroneous results if data are not collected and interpreted 

in the context of a karst conceptual model. In karst terranes, a 

greater emphasis must generally be placed on the identification 

of hydrologic boundaries and subsurface flow paths, contributions of water from various concentrated and diffuse recharge 

sources, the hydraulic properties of conduits, and the springs that 

drain conduit networks. Typically, this emphasis requires the use 

of a multidisciplinary study approach that includes water-tracer 

tests conducted with fluorescent dyes and the analysis of springdischarge and water-chemistry data.

The concepts and methods discussed in this chapter are 

intended to assist the water-resources investigator in determining what types of data-collection activities may be required for 

particular karst water-resources management and protection 

issues, and may aid the planning and implementation of karst 

hydrogeologic studies. The conceptual model of a karst drainage basin, described herein as a fundamental karst mapping 

unit defined by the total area of surface and subsurface drainage that contributes water to a conduit network and its outlet 

spring or springs, may be useful in this regard.

References

Alexander, E.C., Jr., 2002, Scanning spectrofluorophotometer 

methods: Minneapolis, University of Minnesota Department 

of Geology and Geophysics (unpublished document dated 

5/12/02), 10 p.

Alexander, S.C., 2005, Spectral deconvolution and quantification of natural organic material and fluorescent tracer 

dyes, in Beck, B.F., ed., Sinkholes and the engineering and 

environmental impacts of karst, Reston, Virginia: American 

Society of Civil Engineers, Geotechnical Special Publication No. 144, p. 441–448.

Aley, T., 1977, A model for relating land use and groundwater 

quality in southern Missouri, in Dilamarter, R.R., and 

Csallany, S.C., eds., Hydrologic problems in karst regions: 

Bowling Green, Western Kentucky University, p. 232–332.

Aley, T., 1997, Groundwater tracing in the epikarst, in Beck, 

B.F., and Stephenson, J.B., eds., The engineering geology 

and hydrogeology of karst terranes: Rotterdam, Netherlands, A.A. Balkema, p. 207–211. 
108 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Arikan, A., 1988, MODALP—A deterministic rainfall-runoff 

model for large karstic areas: Hydrological Sciences Journal, v. 33, no. 4, p. 401–414.

ASTM Subcommittee D–18–21, 2002, Standard guide for 

design of ground-water monitoring systems in karst and 

fractured-rock aquifers: West Conshohocken, Pa., American 

Society of Testing and Materials, Annual Book of ASTM 

Standards, v. 04.08, ASTM D5717–95, p. 1421–1438.

Atkinson, T.C., 1977, Diffuse flow and conduit flow in limestone terrain in Mendip Hills, Somerset, England: Journal of 

Hydrology, v. 35, p. 93–100.

Atkinson, T.C., Smith, D.I., Lavis, J.J., and Whitaker, R.J., 

1973, Experiments in tracing underground waters in limestones: Journal of Hydrology, v. 19, p. 323–349. 

Baedke, S.J., and Krothe, N.C., 2001, Derivation of effective hydraulic parameters of a karst aquifer from discharge 

hydrograph analysis: Water Resources Research, v. 37, 

no. 1, p. 13–19.

Bassett, J., 1976, Hydrology and geochemistry of the upper 

Lost River drainage basin, Indiana: National Speleological 

Society Bulletin, v. 38, no. 4, p. 79–87.

Bayless, E.R., Taylor, C.J., and Hopkins, M.S., 1994, Directions of ground-water flow and locations of ground-water 

divides in the Lost River watershed near Orleans, Indiana: 

U.S. Geological Survey Water-Resources Investigations 

Report 94–4195, 25 p., 2 pls.

Beck, B.F., ed., 1995, Karst geohazards: Proceedings of the 

Fifth Multidisciplinary Conference on Sinkholes and the 

Engineering and Environmental Impacts of Karst, Gatlinburg, Tenn., April 2–5, 1995: Rotterdam, Netherlands, 

A.A Balkema, 581 p.

Beck, B.F., 2002, Overview of background resources on 

karst research emphasizing obscure and “grey area” documents, in Kuniansky, E.L., ed., U.S. Geological Survey 

Karst Interest Group Proceedings, Shepherdstown, West 

Virginia, August 20–22, 2002: U.S. Geological Survey 

Water-Resources Investigations Report 2002–4174, p. 7.

Beck, B.F., ed., 2003, Sinkholes and the engineering and 

environmental impacts of karst, Proceedings of the Ninth 

Multidisciplinary Conference, September 6–10, 2003, 

Huntsville, Alabama: American Society of Civil Engineers, 

Geotechnical Special Publication no. 122, 737 p.

Beck, B.F., and Stephenson, J.B., eds., 1997, The engineering 

geology and hydrogeology of karst terranes, Proceedings 

of the Sixth Multidisciplinary Conference on Sinkholes 

and the Engineering and Environmental Impacts of Karst, 

Springfield, Missouri, April 6–9, 1997: Rotterdam, Netherlands, A.A Balkema, 516 p.

Beck, B.F., Pettit, A.J., and Herring, J.G., eds., 1999, 

Hydrogeology and engineering geology of sinkholes and 

karst—1999, Proceedings of the Seventh Multidisciplinary 

Conference on Sinkholes and the Engineering and Environmental Impacts of Karst, Harrisburg-Hershey, Pennsylvania, 

April 10–14, 1999: Rotterdam, A.A Balkema, 478 p.

Beven, K.J., 2001, Rainfall-runoff modelling—The primer: 

New York, John Wiley and Sons, Ltd., 360 p.

 Beven, K.J., and Kirkby, M.J., 1979, A physically based, variable contributing area model of basin hydrology: Hydrological Science Bulletin, v. 24, no. 1, p. 43–69.

Bonacci, O., 1993, Karst spring hydrographs as indicators of 

karst aquifers: Hydrological Sciences-Journal-des Sciences 

Hydrologiques, v. 38, no. l, p. 51–62.

Bogli, A., 1980, Karst hydrology and physical speleology: 

New York, Springer-Verlag, 284 p.

Brown, M.C., and Ford, D.C., 1971, Quantitative tracer methods for investigation of karst hydrologic systems: Transactions of the Cave Research Group of Great Britain, v. 13, 

no. 1, p. 37–51.

Brahana, J.V., and Hollyday, E.F., 1988, Dry stream reaches 

in carbonate terranes—Surface indicators of ground-water 

reservoirs: American Water Resources Association Bulletin, 

v. 24, no. 3, p. 577–580.

Campbell, W.C., Lumsdon-West, M., and Davies, S., 2003, 

Geographic information system (GIS) support for karst 

hydrology, in Beck, B.F., ed., Sinkholes and the engineering and environmental impacts of karst, Proceedings of the 

Ninth Multidisciplinary Conference, September 6–10, 2003, 

Huntsville, Alabama: American Society of Civil Engineers, 

Geotechnical Special Publication no. 122, p. 429–438.

Cherkauer, D.S., 2004, Quantifying ground water recharge at 

multiple scales using PRMS and GIS: Ground Water, v. 42, 

no. 1, p. 97–110.

Clark, I., and Fritz, P., 1997, Environmental isotopes in hydrogeology: New York, Lewis Publishers, CRC Press LLC, 

328 p.

Crawford, N.C., 1987, The karst hydrogeology of the Cumberland Plateau escarpment of Tennessee: Nashville, Tennessee 

Department of Conservation, Division of Geology, Report 

of Investigations no. 44, pt. 1, 43 p.

Crawford, N.C., Groves, C.G., Feeney, T.P., and Keller, B.J., 

1987, Agriculture and urban nonpoint source pollution 

impacts on karst aquifers in the Pennyroyal karst region of 

Kentucky: Bowling Green, Western Kentucky University 

Center for Cave and Karst Studies (unpublished contract 

research report prepared for the Division of Water, Kentucky Natural Resources and Environmental Protection 

Cabinet, Frankfort, Kentucky and the Barren River Area 

Development District, Bowling Green, Kentucky), 229 p.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 109

Culver, D.C., and White, W.B., 2004, Encyclopedia of caves: 

Academic Press, Elsevier, 680 p.

Currens, J.C., 1994, Characterization and quantification of 

nonpoint-source pollutant loads in a conduit-flow-dominated karst aquifer underlying an intensive-use agricultural 

region, Kentucky: Lexington, Proceedings of the Kentucky 

Water Resources Symposium, University of Kentucky 

Water Resources Research Institute, p. 3.

 Currens, J.C., and Graham, C.D.R., 1993, Flooding of the 

Sinking Creek karst area in Jessamine and Woodford Counties, Kentucky: Kentucky Geological Survey Report of 

Investigations 7, series XI, 33 p.

Currens, J.C., and Ray, J.A., 1999, Karst atlas for Kentucky, 

in Beck, B.F., Pettit, A.J., and Herring, J.G., eds., Hydrogeology and engineering geology of sinkholes and karst, 

Proceedings of the Seventh Multidisciplinary Conference on 

Sinkholes and the Engineering and Environmental Impacts 

of Karst, April 10–14, 1999, Harrisburg-Hershey, Pennsylvania: Rotterdam, Netherlands, A.A. Balkema, p. 85–90.

Currens, J.C., 2001, Generalized block diagram of the Western 

Pennyroyal Karst: Kentucky Geological Survey, map and 

chart 16, series XII.

Doctor, D.H., and Alexander, E.C., Jr., 2005, Interpretation of 

water chemistry and stable isotope data from a karst aquifer 

according to flow regimes identified through hydrograph 

recession analysis, in Kuniansky, E.L., ed., U.S. Geological 

Survey Karst Interest Group Proceedings, Rapid City, South 

Dakota, September 12–15, 2005: U.S. Geological Survey 

Scientific Investigations Report 2005–5160, p. 82–92.

Dogwiler, T., and Wicks, C.M., 2004, Sediment entrainment 

and transport in fluviokarst systems: Journal of Hydrology, 

v. 295, p. 163–172.

Dooge, J.C.I., 1973, Linear theory of hydrologic systems: 

U.S. Department of Agriculture Technical Bulletin 1468, 

327 p.

Dreiss, S.J, 1982, Linear kernels for karst aquifers: Water 

Resources Research, v. 18, no. 4, p. 865–876.

Dreiss, S.J, 1983, Linear unit-response functions as indicators 

of recharge areas for karst springs: Journal of Hydrology, 

v. 61, p. 31–44.

Dreiss, S.J, 1989, Regional scale transport in a karst aquifer, 2—Linear systems and time moment analysis: Water 

Resources Research, v. 25, no. 1, p. 126–134.

Duley, J.W., 1986, Water tracing using a scanning spectrofluorometer for detection of fluorescent dyes, in Environmental 

Problems in Karst Terranes and their Solutions Conference, 

Bowling Green, Kentucky: Dublin, Ohio, Proceedings of 

the National Water Well Association, October 28–30, 1986, 

p. 389–406.

Felton, G.K., and Currens, J.C., 1994, Peak flow rate and 

recession-curve characteristics of a karst spring in the Inner 

Bluegrass, Central Kentucky: Journal of Hydrology, v. 162, 

p. 99–118.

Field, M.S., 1999a, Quantitative analysis of tracer breakthrough curves from tracing tests in karst aquifers, in

Palmer, A.N., Palmer, M.V., and Sasowsky, I.D., eds., Karst 

modeling: Leesburg, Va., Karst Waters Institute Special 

Publication 5, p. 163–171.

Field, M.S., 1999b, On the importance of stock dye concentrations for accurate preparation of calibration standards, in

Palmer, A.N., Palmer, M.V. and Sasowsky, I.D., eds., Karst 

modeling: Leesburg, Va., Karst Waters Institute, Special 

Publication 5, p. 229.

Field, M.S., 2002a, A lexicon of cave and karst terminology 

with special reference to environmental karst hydrology: 

United States Environmental Protection Agency Publication 

EPA/600/R–02/003, 214 p.

Field, M.S., 2002b, The QTRACER2 program for tracerbreakthrough curve analysis for tracer tests in karstic 

aquifers and other hydrologic systems: U.S. Environmental 

Protection Agency Publication EPA/600/R–02/001, 179 p.

Field, M.S., 2003, Tracer-test planning using the Efficient 

Hydrologic Tracer-Test Design (EHTD) Program: Washington, D.C., U.S. Environmental Protection Agency, Office of 

Research and Development, National Center for Environmental Assessment, EPA/600/R–03/034, 103 p.

Field, M.S., 2006, Tracer-test design for losing stream-aquifer 

systems: International Journal of Speleology, v. 35, no. 1, 

p. 25–36.

Field, M.S., and Nash, S.G., 1997, Risk assessment methodology for karst aquifers—(1) Estimating karst conduit-flow 

parameters: Environmental Monitoring and Assessment, 

v. 47, no. 1, p. 1–27.

Field, M.S., Wilhelm, R.G., Quinlan, J.F., and Aley, T.J., 1995, 

An assessment of the potential adverse properties of fluorescent tracer dyes used for groundwater tracing: Environmental Monitoring and Assessment, v. 38, no. 1, p. 75–96.

Ford, D.C., 1999, Perspectives in karst hydrogeology and cavern genesis, in Palmer, A.N., Palmer, M.V., and Sasowsky, 

I.D., eds., Karst modeling: Leesburg, Va., Karst Waters 

Institute Special Publication 5, p. 17–29.

Ford, Derek, and Williams, P.W., 1989, Karst geomorphology 

and hydrology: London, Unwin Hyman, 601 p.

George, A.I., 1989, Caves and drainage north of the Green 

River in White, W.B., and White, E.L., eds., Karst hydrology concepts from the Mammoth Cave area: New York, 

Van Nostrand Reinhold, p. 189–222.
110 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Ginsberg, M., and Palmer, A., 2002, Delineation of source-water 

protection areas in karst aquifers of the Ridge and Valley and 

Appalachian Plateaus Physiographic Provinces—Rules of 

thumb for estimating the capture zones of springs and wells: 

U.S. Environmental Protection Agency EPA 816–R–02–015, 

41 p.

Greene, E.A., 1997, Tracing recharge from sinking streams 

over spatial dimensions of kilometers in a karst aquifer: 

Ground Water, v. 35, no. 5, p. 898–904.

Greene, E.A., Shapiro, A.M., and Carter, J.M., 1999, Hydrogeologic characterization of the Minnelusa and Madison 

aquifers near Spearfish, South Dakota: U.S. Geological Survey Water-Resources Investigations Report 98–4156, 64 p.

Gunn, J., 1983, Point-recharge of limestone aquifers—A 

model from New Zealand karst: Journal of Hydrology, 

v. 61, p. 19–29.

Gunn, J., 1986, A conceptual model for conduit flow dominated karst aquifers, in Gunay, G., and Johnson, A.I., eds., 

Karst water resources, Proceedings of the International 

Symposium, Ankara, Turkey, July 1985: International 

Association of Hydrological Sciences Publication 161, 

p. 587–596.

Hauns, M., Jeannin, P.-Y., and Atteia, O., 2001, Dispersion, 

retardation and scale effect in tracer breakthrough curves in 

karst conduits: Journal of Hydrology, v. 241, p. 177–193.

Hess, J.W., and White, W.B., 1989, Water budget and physical hydrology, in White, W.B., and White, E.L., eds., 

Karst hydrology concepts from the Mammoth Cave area: 

New York, Van Nostrand Reinhold, p. 105–126.

Howcroft, W.D., 1992, Ground water flow and water resources 

investigation of the Auburn, Summers, and Shakertown 

Springs karst groundwater basins, Logan and Simpson 

Counties, Kentucky: Bowling Green, Western Kentucky 

University, Department of Geography, unpublished thesis, 

128 p.

Imes, J.L., Schumacher, J.G., and Kleeschulte, M.J., 1996, 

Geohydrologic and water-quality assessment of the Fort 

Leonard Wood Military Reservation, Missouri, 1994–95: 

U.S. Geological Survey Water-Resources Investigations 

Report 96–4270, 134 p.

Jones, W.K., 1984a, Dye tracer tests in karst areas: National 

Speleological Society Bulletin, v. 46, p. 3–9.

Jones, W.K., 1984b, Analysis and interpretation of data from 

tracer tests in karst areas: National Speleological Society 

Bulletin, v. 46, p. 41–47.

Jones, W.K., 1997, Karst hydrology atlas of West Virginia: 

Leesburg, Va., Karst Waters Institute Special Publication 4, 

111 p.

Jones, W.K., Culver, D.C., and Herman, J.S., eds., 2004, 

Epikarst, Proceedings of the 2003 Epikarst symposium, 

October 1–4, 2003, Shepherdstown, West Virginia, USA: 

Leesburg, Va., Karst Waters Institute Special Publication 9, 

160 p.

Kasnavia, T., Vu, D., and Sabatini, D.A., 1999, Fluorescent 

dye and media properties affecting sorption and tracer selection: Ground Water, v. 37, no. 3, p. 376–381.

Käss, W., 1998, Tracing technique in geohydrology: Rotterdam, Netherlands, A.A. Balkema; Brookfield, Vermont, 

A.A. Balkema Publishers, 581 p.

Katz, B.G., 2005, Demystification of ground-water flow and 

contaminant movement in karst systems using chemical and 

isotopic tracers, in Kuniansky, E.L., ed., U.S. Geological 

Survey Karst Interest Group Proceedings, Shepherdstown, 

West Virginia August 20–22, 2002: U.S. Geological Survey 

Water-Resources Investigations Report 2002–4174, p. 13–19.

Katz, B.G., Coplen, T.B., Bullen, T.D., and Davis, J.H., 1997, 

Use of chemical and isotopic tracers to characterize the 

interactions between ground water and surface water in 

mantled karst: Ground Water, v. 35, no. 6, p. 1014–1028.

Kilpatrick, F.A., and Cobb, E.D., 1984, Measurement of 

discharge using tracers: U.S. Geological Survey Open-File 

Report 84–136, 73 p.

Kincaid, T.R., Hazlett, T.J., and Davies, G.J., 2005, Quantitative groundwater tracing and effective numerical modeling 

in karst—An example from the Woodville Karst Plain of 

North Florida, in Beck, B.F., ed., Sinkholes and the engineering and environmental impacts of karst, Proceedings 

of the 10th Multidisciplinary Conference, San Antonio, 

Texas, September 24–28, 2005: Geological Institute of the 

American Society of Civil Engineers, Geotechnical Special 

Publication no. 144, p. 114–121.

Klimchouk, A.B., 2004, Towards defining, delimiting and 

classifying epikarst—Its origin, processes and variants of 

geomorphic evolution, in Jones, W.K., Culver, D.C., and 

Herman, J., eds., Epikarst, Proceedings of the 2003 Epikarst 

symposium, October 1–4, 2003, Shepherdstown, West 

Virginia, USA: Karst Waters Institute Special Publication 9, 

p. 23–35.

Klimchouk, A.B., Ford, D.C., Palmer, A.N., and Dreybrodt, 

W., 2000, Speleogenesis evolution of karst aquifers: 

National Speleological Society, 527 p.

Kresic, N., 1997, Quantitative solutions in hydrogeology and 

groundwater modeling: Boca Raton, CRC Lewis Publishers, 

461 p.

Kuniansky, E.L., ed., 2001, U.S.Geological Survey Karst 

Interest Group Proceedings, St. Petersburg, Florida, February 13–16, 2001: U.S. Geological Survey Water-Resources 

Investigations Report 2001–4011, 211 p.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 111

Kuniansky, E.L., ed., 2002, U.S.Geological Survey Karst 

Interest Group Proceedings, Shepherdstown, West Virginia, August 20–22, 2002: U.S. Geological Survey 

Water-Resources Investigations Report 2002–4174, 89 p.

Kuniansky, E.L. ed., 2005, U.S.Geological Survey Karst Interest Group Proceedings, Rapid City, South Dakota, September 12–15, 2005: U.S. Geological Survey Scientific Investigations Report 2005–5160, 296 p.

Kuniansky, E.L., Fahlquist, L., and Ardis, A.F., 2001, Travel times 

along selected flow paths of the Edwards aquifer, Central Texas, 

in Kuniansky, E.L., ed., U.S. Geological Survey Karst Interest 

Group Proceedings, St. Petersburg, Florida, February 13–16, 

2001: U.S. Geological Survey Water-Resources Investigations 

Report 2001–4011, p. 69–77.

Lakey, B.L., and Krothe, N.C., 1996, Stable isotope variation 

of storm discharge from a perennial karst spring, Indiana: 

Water Resources Research, v. 32, no. 2, p. 721–731.

Lane, S.R., and Smart, C.C., 1999, A method for correction 

of variable background fluorescence in filter fluorometry, 

in Beck, B.F., Pettit, A.J., and Herring, J.G., eds., Hydrology and engineering geology of sinkholes and karst—1999, 

Proceedings of the Seventh Multidisciplinary Conference, 

Harrisburg-Hershey Pennsylvania, April 10–14, 1999: Rotterdam, Netherlands, A.A Balkema, p. 301–306.

Leavesley, G.H., Lichty, R.W., Troutman, B.M., and Saindon, 

L.G., 1983, Precipitation-Runoff Modeling System—User’s 

manual: U.S. Geological Survey Water-Resources Investigations Report 83–4238, 207 p.

Lee, E.S., and Krothe, N.C., 2001, A four-component mixing 

model for water in a karst terrain in south-central Indiana, 

USA, using solute concentration and stable isotopes as tracers: Chemical Geology, v. 179, p. 129–143.

Liedl, R., Sauter, M., Hückinghaus, D., Clemens, T., and 

Teutsch, G., 2003, Simulation of the development of karst 

aquifers using a coupled continuum pipe flow model: Water 

Resources Research, v. 39, no. 3, p. 1057.

Long, A.J., and Derickson, R.G., 1999, Linear systems analysis 

in a karst aquifer: Journal of Hydrology, v. 219, p. 206–217. 

Meiman, J., and Ryan, M.T., 1999, The development of 

basin-scale conceptual models of the active-flow conduit 

system, in Palmer, A.N., Palmer, M.V., and Sasowsky, I.D., 

eds., Karst modeling: Leesburg, Va., Karst Waters Institute 

Special Publication 5, p. 203–212.

Meinzer, O.E., 1927, Large springs in the United States: 

U.S. Geological Survey Water-Supply Paper 557, 94 p.

Milanovic ́, P.T., 1981a, Water regime in deep karst—Case 

study of the Ombla Spring drainage area, in Yevjevich, V., 

ed., Karst hydrology and water resources, Proceedings of 

the U.S.-Yugoslavian Symposium, Dubrovnik, 1975: Littleton, Colo., Water Resources Publication, p. 165–191.

Milanovic ́, P.T., 1981b, Karst hydrogeology: Littleton, Colo., 

Water Resources Publication, 434 p.

Mull, D.S., Smoot, J.L., and Liebermann, T.D., 1987, Dye 

tracing techniques used to determine ground-water flow in 

a carbonate aquifer system near Elizabethtown, Kentucky: 

U.S. Geological Survey Water-Resources Investigations 

Report 87–4174, 95 p., 2 pls.

Mull, D.S., Liebermann, T.D., Smoot, J.L., and Woosley, Jr., 

L.H., 1988, Application of dye-tracing techniques for determining solute-transport characteristics of ground water in 

karst terranes: Atlanta, Ga., U.S. Environmental Protection 

Agency, EPA Report 904/6–88–001, 103 p.

National Academy of Sciences, 2004, Groundwater fluxes 

across interfaces—Committee on hydrologic science: 

Washington, D.C., National Research Council, National 

Academies Press, 100 p.

National Ground Water Association, 1991, Proceedings of 

the Third Conference on Hydrogeology, Ecology, Monitoring, and Management of Ground Water in Karst Terranes, 

December 4–6, 1991, Nashville, Tennessee: Dublin, Ohio, 

National Ground Water Association, 793 p.

National Water Well Association, 1986, Proceedings of the 

Environmental Problems in Karst Terranes and Their Solutions Conference, October 28–30, 1986, Bowling Green, 

Kentucky: Dublin, Ohio, National Water Well Association, 

525 p.

National Water Well Association, 1988, The Proceedings 

of the Second Conference on Environmental Problems in 

Karst Terranes and Their Solutions, November 16–18, 1988, 

Nashville, Tennessee: Dublin, Ohio, National Water Well 

Association, 441 p.

Neuman, S.P., and de Marsily, G., 1976, Identification of 

linear systems response by parametric programming: Water 

Resources Research, v. 12, no. 2, p. 253–262.

Padilla, A., Pulio-Bosch, A., and Mangin, A., 1994, Relative 

importance of baseflow and quickflow from hydrographs of 

karst springs: Ground Water, v. 32, p. 267–277. 

Paillet, F.L., 2001, Borehole geophysical applications in 

karst hydrology, in Kuniansky, E.L., ed., U.S. Geological 

Survey Karst Interest Group Proceedings, St. Petersburg, 

Florida, February 13–16, 2001: U.S. Geological Survey Water-Resources Investigations Report 2001–4011, 

p. 116–123.

Palmer, A.N., 1991, Origin and morphology of limestone 

caves: Geological Society of America Bulletin, v. 103, 

p. 1–21.

Palmer, A.N., 1999, Patterns of dissolution porosity in carbonate rocks, in Palmer, A.N., Palmer, M.V., and Sasowsky, 

I.D., eds., Karst modeling: Leesburg, Va., Karst Waters 

Institute Special Publication 5, p. 71–78.
112 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Pinault, J.L., Plagnes, V., Aquilina, L., and Bakalowicz, M., 

2001, Inverse modeling of the hydrological and hydrochemical behavior of hydrosystems—Characterization of karst 

system functioning: Water Resources Research, v. 37, no. 8, 

p. 2191–2204.

Quinlan, J.F., 1970, Central Kentucky karst: Méditerranée 

Études et Travaux, v. 7, p. 235–253.

Quinlan, J.F., 1989, Ground-water monitoring in karst 

terranes—Recommended protocols and implicit assumptions: Las Vegas, Nev., U.S. Environmental Protection 

Agency, Environmental Monitoring Systems Laboratory, 

EPA/600/X–89/050, 79 p.

Quinlan, J.F., and Ewers, R.O., 1989, Subsurface drainage in 

the Mammoth Cave area, in White, W.B., and White, E.L., 

eds., Karst hydrology concepts from the Mammoth Cave 

area: New York, Van Nostrand Reinhold, p. 65–104.

Quinlan, J.F., Ewers, R.O., Ray, J.A., Powell, R.L., and 

Krothe, N.C., 1983, Groundwater hydrology and geomorphology of the Mammoth Cave region, Kentucky, and of the 

Mitchell Plain, Indiana, in Shaver, R.H., and Sunderman, 

V.A., eds., Field trips in midwestern geology: Geological 

Society of America, v. 2, p. 1–85.

Quinlan, J.F., and Ray, J.A., 1989, Groundwater basins in the 

Mammoth Cave region, Kentucky, showing springs, major 

caves, flow routes, and potentiometric surface: Mammoth 

Cave, Ky., Friends of the Karst Occasional Publication 

no. 2, 1 pl.

Quinlan, J.F., and Ray J.A., 1995, Normalized base-flow 

discharge of ground-water basins—A useful parameter for 

estimating recharge area of springs and for recognizing 

drainage anomalies in karst terranes, in Beck, B., ed., Karst 

geohazards, Proceedings of the Fifth Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst, April 2–5, 1995, Gatlinburg, Tennessee: Rotterdam, Netherlands, A.A. Balkema, p. 149–164.

Quinlan, J.F., Ray, J.A., and Schindel, G.M., 1995, Intrinsic 

limitations of standard criteria and methods for delineation 

of groundwater-source protection areas (springhead and 

wellhead protection areas) in carbonate terranes—Critical 

review, technically-sound resolution of limitations, and 

case study in a Kentucky karst, in Beck, B.F., and Pearson, 

F.M., eds., Karst geohazards engineering and environmental 

problems in karst terrane: A.A. Balkema, Rotterdam, Netherlands, p. 165–176.

Ray, J.A., 1994, Surface and subsurface trunk flow, Mammoth 

Cave, Kentucky: Mammoth Cave, Ky., Proceedings of the 

Third Mammoth Cave National Park Science Conference, 

Mammoth Cave National Park, p. 175–187.

Ray, J., 1999, A model of karst drainage basin evolution, interior low plateaus, USA, in Palmer, A.N., Palmer, M.V., and 

Sasowsky, I.D., eds., Karst modeling: Leesburg, Va., Karst 

Waters Institute Special Publication 5, p. 58.

Ray, J., 2001, Spatial interpretation of karst drainage basins: 

in Beck, B.F., and Herring, J.G., eds., Geotechnical and 

environmental applications of karst geology and hydrology, 

Proceedings of the Eighth Multidisciplinary Conference on 

Sinkholes and the Environmental and Engineering Impacts 

of Karst, April 1–4, 2001, Louisville, Kentucky: Lisse, 

Balkema Publishers, p. 235–244.

Ray, J.A., and Currens, J.C., 1998, Mapped karst ground-water 

basins in the Beaver Dam 30 × 60 minute quadrangle: Kentucky Geological Survey Map and Chart, ser. 11, map and 

chart 19, scale 1:100,000.

Rendell, D., 1987, Fluorescence and phosphorescence—

Analytical chemistry by open learning series: London, 

Thames Polytechnic, John Wiley and Sons, 419 p.

 Rorabaugh, M.I., 1964, Estimating changes in bank storage 

as ground-water contribution to streamflow: International 

Association Scientific Hydrological Publications 63, 

p. 432–441.

Rovey, C.W., II, and Cherkauer, D.S., 1994, Relation 

between hydraulic conductivity and texture in a carbonate aquifer: regional continuity: Groundwater v. 32, no. 2, 

p. 227–238.

Ryan, M.T., and Meiman, J., 1996, An examination of shortterm variations in water quality at a karst spring in Kentucky: Ground Water, v. 34, no. 1, p. 23–30.

Sauter, M., 1991, Assessment of hydraulic conductivity in a 

karst aquifer at local and regional scale, in Proceedings of 

the Third Conference on Hydrogeology, Ecology, Monitoring, and Management of Ground Water in Karst Terranes 

December 4–6, 1991, Nashville, Tennessee: National 

Ground Water Association, p. 39–56.

Sauter, M., 1992, Assessment of hydraulic conductivity in 

a karst aquifer at local and regional scale: Ground Water 

Management, v. 10, p. 39–57.

Scanlon, B.R., Mace, R.E., Barrett, M.E, and Smith, B., 2003, 

Can we simulate regional groundwater flow using equivalent porous media models? Case study, Barton Springs 

Edwards aquifer, USA: Journal of Hydrology, v. 276, 

p. 137–158.

Scanlon, B.R., and Thrailkill, 1987, Chemical similarities 

among physically distinct spring types in a karst terrain: 

Journal of Hydrology, v. 89, p. 259–279.
Hydrogeologic Characterization and Methods Used in the Investigation of Karst Hydrology 113

Schindel, G.M., Ray, J.A., and Quinlan, J.F., 1995, Delineation 

of the recharge area for Rio Springs, Kentucky—An EPA 

demonstration project in wellhead (springhead) protection 

for karst terranes, in Beck, B.F., and Pearson, F.M., eds., 

Karst geohazards engineering and environmental problems 

in karst terrane: Rotterdam, Netherlands, and Brookfield, 

Vermont, A.A. Balkema, p. 165–176.

 Shapiro, A.M., 2001, Effective matrix diffusion in kilometer-scale transport in fractured crystalline rock: Water 

Resources Research, v. 37, p. 507–522.

 Shevenell, L., 1996, Analysis of well hydrographs in a karst 

aquifer—Estimates of specific yields and continuum transmissivities: Journal of Hydrology, v. 174, p. 331–355.

Shuster, E.T., and White, W.B., 1971, Seasonal fluctuations 

in the chemistry of limestone springs—A possible means 

of characterizing carbonate aquifers: Journal of Hydrology, 

v. 14, p. 93–128.

Smart, C.C., 1988, A deductive model of karst evolution based 

on hydrological probability: Earth Surface Processes and 

Landforms, v. 13, p. 271–288.

 Smart, C.C., 1998, Artificial tracer techniques for the determination of the structure of conduit aquifers: Ground Water, 

v. 26, p. 445–453.

Smart, C.C., 2005, Error and technique in fluorescent dye 

tracing, in Beck, B.F., ed., Sinkholes and the engineering 

and environmental impacts of karst: Reston, Va., American 

Society of Civil Engineers, Geotechnical Special Publication no. 144, p. 500–509.

Smart, C.C., and Ford, D.C., 1982, Quantitative dye tracing 

in a glacierized alpine karst: Beitraege Zur Geologie der 

Schweiz—Hydrologie, v. 28, no. 1, p. 191–200.

Smart, C.C., and Karunaratne, K.C., 2002, Characterization 

of fluorescence background in dye tracing: Environmental 

Geology, v. 42, p. 492–498.

Smart, C.C., and Simpson, B., 2001, An evaluation of the performance of activated charcoal in detection of fluorescent 

compounds in the environment, in Beck and Herring, eds., 

Geotechnical and environmental applications of karst geology and hydrology: Rotterdam, Netherlands, A.A Balkema, 

p. 265–270.

Smart, C.C., and Simpson, B., 2002, Detection of fluorescent compounds in the environment using granular activated charcoal detectors: Environmental Geology, v. 42, 

p. 538–545.

Smart, C.C., and Smart, P.L., 1991, Correction of background 

interference and cross-fluorescence in filter fluorometric 

analysis of water-tracer dyes, in Proceedings of the Third 

Conference on Hydrogeology, Ecology, Monitoring, and 

Management of Ground Water in Karst Terranes, December 4–6, 1991, Nashville, Tennessee: National Ground 

Water Association, p. 475–491.

Smart, C.C., Zabo, L., Alexander, E.C., Jr., and Worthington, 

S.R.H., 1998, Some advances in fluorometric techniques for 

water tracing: Environmental Monitoring and Assessment, 

v. 53, p. 305–320.

Smart, P.L., 1972, A laboratory evaluation of the use of 

activated carbon for the detection of tracer dye Rhodamine 

WT: University of Alberta, Canada, (unpublished Master's 

thesis).

Smart, P.L., and Laidlaw, I.M.S., 1977, An evaluation of 

some fluorescent dyes for water tracing: Water Resources 

Research, v. 13, p. 15–33.

Smoot, J.L., Mull, D.S., and Liebermann, T.D., 1987, Quantitative dye tracing techniques for describing the solute transport characteristics of ground-water flow in karst terrane, in

Proceedings of the Second Multidisciplinary Conference on 

Sinkholes and the Environmental Impacts of Karst, Orlando, 

Florida, February 9–11, 1987: National Water Well Association, p. 269–275.

Steinheimer, T.R., and Johnson, S.M., 1986, Investigation of 

the possible formation of diethylnitrosamine resulting from 

the use of rhodamine WT as a tracer in river waters: U.S. 

Geological Survey Water-Supply Paper 2290, p. 37–49.

Stoica, P., and Soderstrom, T., 1982, Instrumental variable 

methods for identification of Hammerstein system: International Journal of Control, v. 35, p. 459–476.

Streltsova, T.D., 1988, Well testing in heterogeneous formations: New York, John Wiley and Sons, 413 p.

Sukhodolov, A.N., Nikora, V.I., Rowin ́ski, P.M., and 

Czernuszenko, W., 1997, A case study of longitudinal 

dispersion in small lowland rivers: Water Environmental 

Resources, v. 97, p. 1246–1253.

Taylor, C.J., and McCombs, G.K., 1998, Recharge-area delineation and hydrology, McCraken Springs, Fort Knox Military Reservation, Meade County, Kentucky: U.S. Geological 

Survey Water-Resources Investigations Report 98–4196, 

12 p., 1 pl.

Taylor, C.J., Nelson, H.L., Hileman, G., and Kaiser, W.P., 

2005, Hydrogeologic framework mapping of shallow, 

conduit-dominated karst—Components of a regional GISbased approach, in Kuniansky, E.L., ed., U.S. Geological 

Survey Karst Interest Group Proceedings, Rapid City, South 

Dakota, September 12–15, 2005: U.S. Geological Survey 

Scientific Investigations Report 2005–5160, p. 103–113.
114 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Teutsch, G., 1992, Groundwater modeling in karst terranes—

Scale effects, data acquisition, and field validation: Ground 

Water Management, v. 10, p. 17–35.

Teutsch G., and Sauter, M., 1991, Groundwater modeling in karst terranes—Scale effects, data acquisition, and 

field verification, Proceedings of the Third Conference on 

Hydrogeology, Ecology, Monitoring, and Management of 

Ground Water in Karst Terranes, Nashville, Tennessee, 

December 4–6, 1991: National Ground Water Association, 

p. 17–54.

Thrailkill, J., 1985, The Inner Bluegrass karst region, in

Dougherty, P.H., ed., Caves and karst of Kentucky: Kentucky Geological Survey Special Publication 12, Series IX, 

p. 28–62.

Toth, J., 1963, A theoretical analysis of groundwater flow in 

small drainage basins: Journal of Geophysical Research, 

v. 68, p. 211–222.

Trc ́ek, B., and Krothe, N.C., 2002, The importance of 

three and four-component storm hydrograph separation techniques for karst aquifers, in Gabrovšek, Franci, 

ed., Evolution of karst—From prekarst to cessation: 

Postojna-Ljubljana Založba ZRC, p. 395–401.

Tucker, R.B., and Crawford, N.C., 1999, Non-linear curvefitting analysis as a tool for identifying and quantifying 

multiple fluorescent tracer dyes present in samples analyzed 

with a spectrofluorophotometer and collected as part of a 

dye tracer study of groundwater flow, in Beck, B.F., Pettit, 

A.J., and Herring, J.G., eds., Hydrology and engineering 

geology of sinkholes and karst—1999: Harrisburg-Hershey, 

Pennsylvania, Proceedings of the Seventh Multidisciplinary 

Conference, April 10–14, 1999, p. 307–312.

U.S. Geological Survey, 2005, User’s Manual for the National 

Water Information System of the U.S. Geological Survey, 

Ground-Water Site-Inventory System: U.S. Geological 

Survey Open-File Report, version 4.5, available at <http://

wwwnwis.er.usgs.gov/nwisdocs4_5/gw/gw_complete.pdf>

Vandike, J.E., 1992, The hydrogeology of the Bennett Spring 

area, Laclede, Dallas, Webster, and Wright Counties, Missouri: Missouri Department of Natural Resources Division of Geology and Land Survey Water Resources Report 

no. 38, 112 p.

White, W.B. 1988, Geomorphology and hydrology of karst 

terrains: New York, Oxford University Press, 464 p.

White, W.B., 1993, Analysis of karst aquifers, in Alley, W.M., 

ed., Regional ground-water quality: New York, Van Nostrand Reinhold, p. 471–489.

White, W.B., 1999, Conceptual models for karstic aquifers, in

Palmer, A.N., Palmer, M.V., and Sasowsky, I.D., eds., Karst 

modeling: Leesburg, Va., Karst Waters Institute Special 

Publication 5, p. 11–16.

White, W.B., and Schmidt, V.A., 1966, Hydrology of a 

karst area in east-central West Virginia: Water Resources 

Research, v. 2, no. 3, p. 549–560.

White, W.B., and White, E.L., eds., 1989, Karst hydrology—

Concepts from the Mammoth Cave area: New York, 

Van Nostrand Reinhold, 346 p.

Wicks, C.M., and Hoke, J.A., 2000, Prediction of the quantity 

and quality of Maramec Spring water: Ground Water, v. 38, 

no. 2, p. 218–225.

Williams, P.W, 1983, The role of the subcutaneous zone in 

karst hydrology: Journal of Hydrology, v. 61, p. 45–67.

Wilson, J.F., Jr., Cobb, E.D., and Kilpatrick, F.A., 1986, 

Fluorometeric procedures for dye tracing: U.S. Geological Survey Techniques for Water Resources Investigations, 

book 3, chap. A12, 34 p.

Worthington, S.R.H., 1991, Karst hydrology of the Canadian 

Rocky Mountains: Hamilton, Ontario, Canada, McMaster 

University, unpublished Ph. D. dissertation, 380 p.

Worthington, S.R.H., 1999, A comprehensive strategy for 

understanding flow in carbonate aquifers, in Palmer, A.N., 

Palmer, M.V., and Sasowsky, I.D., eds., Karst modeling: 

Leesburg, Va., Karst Waters Institute Special Publication 5, 

p. 30–37.

Worthington, S.R.H., 2003, Numerical simulation of the aquifer 

at Mammoth Cave, in Kambesis, P., Meiman, J., and Groves, 

C., eds., Proceedings of the International Conference on Karst 

Hydrogeology and Ecosystems, Bowling Green, Kentucky, 

USA, June 3–6, 2003: Western Kentucky University, Hoffman Environmental Research Institute, p. 10.

Worthington, S.R.H., Davies, G.J., and Ford, D.C., 2000, 

Matrix, fracture and channel components of storage and 

flow in a Paleozoic limestone aquifer, in Sasowsky, I.D., 

and Wicks, C.M., eds., Groundwater flow and contaminant 

transport in carbonate aquifers: Rotterdam, Netherlands, 

A.A. Balkema, p. 113–128.

Worthington, S.R.H., and Smart, C.C., 2003, Empirical determination of tracer mass for sink to spring tests in karst, in

Beck, B., ed., Sinkholes and the engineering and environmental impacts of karst: Huntsville, Ala., Proceedings of the 

Ninth Multidisciplinary Conference, September 6–10, 2003, 

p. 287–295.

Zhang, Y.K., and Bai, E.W., 1996, Simulation of spring discharge from a limestone aquifer in northeastern Iowa with 

an identification scheme, in Kovar, Karl, and van der Heijde, 

Paul, eds., Calibration and reliability in groundwater modeling: Golden, Colo., Proceedings of ModelCARE96 Conference, September 1996, IAHS Publication no. 237, p. 31–40.

Zhang, Y.K., Bai, E.W., Rowden, R., and Liu, H., 1995, Simulation of spring discharge from a limestone aquifer in Iowa, 

USA: Hydrogeology Journal, v. 4, no. 4, p. 41–54.
Analysis of Temperature Gradients 

to Determine Stream Exchanges

with Ground Water

By James E. Constantz, Richard G. Niswonger, and Amy E. Stewart

Chapter 4 of

Field Techniques for Estimating Water Fluxes Between 

Surface Water and Ground Water

Edited by Donald O. Rosenberry and James W. LaBaugh

Techniques and Methods Chapter 4–D2

U.S. Department of the Interior

U.S. Geological Survey
Contents

Introduction.................................................................................................................................................117

Heat Transfer During Stream/Ground-Water Exchanges ...................................................................117

Quantitative Analyses of Heat as a Ground-Water Tracer Near a Stream......................................118

Temperature Instrumentation..................................................................................................................120

Background........................................................................................................................................120

Direct Versus Indirect Measurements..........................................................................................120

Methods to Analyze Streambed Temperatures ....................................................................................122

Example Sites .............................................................................................................................................123

Bear Canyon, New Mexico .............................................................................................................123

Santa Clara River, California ...........................................................................................................125

Summary......................................................................................................................................................126

References..................................................................................................................................................126

Figures

1. A qualitative description of thermal and hydraulic responses to four possible 

states of a streambed ..............................................................................................................121

2. The streambed temperature profiles for a losing stream compared with a 

gaining stream for the annual example and the diurnal example....................................122

3. The simulated temperature profile below the Rio Grande, central New Mexico..........123

4. The streambed temperature patterns resulting from late stages of continuous 

spring streamflows...................................................................................................................124

5. The streambed temperature patterns compared with optimized (simulated) 

sediment temperatures............................................................................................................124

6. The measured sediment temperatures compared with simulated streambed 

temperatures .............................................................................................................................125

7. A comparison of streambed temperatures measured directly in the sediments 

and temperatures measured inside the observation well for observation 

site SCR5 ....................................................................................................................................126
Introduction

Heat flows continuously between surface water and 

adjacent ground water, and as a consequence, provides an 

opportunity to use heat as a natural tracer of water movement 

between the surface and the underlying sediments. By the 

early 1900s, researchers intuitively understood that heat is 

simultaneously transferred during the course of water movement through sediments and other porous bodies (Bouyoucos, 

1915). Examination of temperature patterns provided qualitative and quantitative descriptions of an array of groundwater-flow regimes, ranging from those beneath rice paddies 

to those beneath volcanoes. Quantitative analysis of heat 

and water flow was introduced via analytical and numerical solutions to the governing partial differential equations. 

These quantitative analyses often relied on field measurements for parameter identification and accurate predictions 

of flow rates and directions. Because field measurements of 

temperature had to be made manually, however, the data were 

sparse. Early numerical simulation of heat and mass groundwater transport required significant computational resources, 

which limited modeling to conceptual demonstrations. As a 

consequence of these challenges, the use of heat as a tracer 

of ground-water movement was confined to isolated research 

projects, which could demonstrate only the feasibility of the 

method rather than progressing toward a routine use of the 

technique. Recently, both the measurement of temperature 

and the simulation of heat and water transport have benefited 

from significant advances in data acquisition and computer 

resources. This has afforded the opportunity for routine use of 

heat as a tracer in a variety of hydrological regimes. The measurement of heat flow is particularly well suited for investigations of stream/ground-water exchanges. Dynamic temperature 

patterns between a stream and the underlying sediments are 

typical, because of large stream surface area to volume ratios 

relative to many other surface-water bodies. Heat is a naturally occurring tracer, free from (real or perceived) issues of 

contamination associated with the use of chemical tracers in 

stream environments. The use of heat as a tracer relies on the 

measurement of temperature gradients, and temperature is an 

extremely robust property to monitor. Temperature data are 

immediately available as opposed to most chemical tracers, 

many of which require laboratory analysis. The recent publication of numerous case studies (for example, Su and others, 

2004; Burow and others, 2005) greatly extends the temporal 

range and the spatial scale over which temperature gradients 

have been analyzed to use heat as a natural tracer of groundwater movement near streams. This chapter reviews early 

work that addresses heat as a tracer in hydrological investigations of the near-surface environment, that describes recent 

advances in the field, and that presents selected new results 

designed to identify the broad application of heat as a tracer to 

investigate stream/ground-water exchanges. An overview of 

field techniques for estimating water fluxes between surface 

water and ground water is provided here; for a comprehensive 

discussion with numerous case studies, see Stonestrom and 

Constantz (2003).

Heat Transfer During Stream/

Ground-Water Exchanges

When water is present in a stream channel, heat and 

water transfer because of vapor movement in the streambed 

sediments generally is negligible relative to heat and water 

transfer because of liquid water movement. This eliminates 

the need to address the complex processes of nonisothermal 

vapor dynamics in porous material when describing heat and 

water movement below streams. Within the streambed, heat 

is transferred into and through sediments as a result of three 

heat-transfer mechanisms. Radiative heat transfer occurs as 

solar radiation is adsorbed by the streambed surface. This is 

the dominant mechanism for a dry streambed, but is usually a 

small component of heat transfer for the streambed beneath a 

flowing stream. Heat conduction occurs as diffusive molecular transfer of thermal energy between the streambed surface 

and the underlying sediments. Heat convection and advection 

often are used interchangeably in hydrology to indicate heat 

Chapter 4

Analysis of Temperature Gradients to Determine Stream 

Exchanges with Ground Water

By James E. Constantz,1 Richard G. Niswonger,2 and Amy E. Stewart3

1

U.S. Geological Survey, Menlo Park, CA 94025.

2

U.S. Geological Survey, Carson City, NV 89706.

3

Now with Philip Williams and Associates, San Francisco, CA 94108.
118 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

transfer resulting from the movement of water (or air). For the 

present work, it is advantageous to partition their definitions as 

follows. Heat convection is defined as heat transfer occurring 

because of the movement of water (or air) above a streambed 

of dissimilar temperature. Heat advection is defined as the 

heat transfer that occurs during the movement of water (or air) 

through the streambed. This alternative definition is useful for 

the application of heat as a tracer in examining stream/ground 

water interaction because it aids in delineating between heat 

transfers as a result of ground-water movement (advection) in 

contrast to surface-water movement (convection). Thus, heat 

conduction, convection, and advection all contribute to heat 

transfer across the stream/streambed boundary, but determination of heat advection is the focus in examining stream/

ground-water interaction.

Commonly, all three heat-transfer mechanisms occur 

simultaneously within stream environments. For example, all 

three mechanisms occur in a losing stream reach as water infiltrates into the streambed, then percolates through the sediments, 

potentially recharging the water table. Convective heat transfer occurs between the stream and sediments as stream water 

flows over the sediments. As a result of this convection transfer, 

conductive heat exchange occurs between the surface sediments 

and sediments at depth. Simultaneously, advective heat transport 

occurs as water infiltrates into the sediment and percolates in a 

downward (but usually not vertical) direction. The daily and (or) 

annual temperature extremes are attenuated and delayed with 

depth in the streambed sediments. The attenuation of temperature extremes is determined by the bulk volumetric heat capacity of the sediments as heat is rapidly exchanged at the pore 

scale. The delay or lag in temperature extremes is controlled 

by the rate of downward heat transfer, which is dependent on 

the thermal conductivity of the sediments and the pore-water 

velocity through the sediments. The greater the heat transfer, the 

greater the depth of penetration and the shorter the time lag of 

temperature extremes. In the vicinity of streams, heat usually is 

transported more rapidly by moving water than through molecular diffusion and, as a result, higher streambed infiltration rates 

result in the deeper penetration and shorter lags in temperature 

extremes (for example, Lapham, 1989; Silliman and others, 

1995). For a neutral stream reach (one neither gaining nor losing 

flow), the streambed-temperature gradients are created by convective heat transfer from the stream to the streambed surface, 

and heat transport into the sediment is determined by heat conduction alone. (Thus, if the Fourier equation for conductive heat 

transfer can explain the temperature patterns within a streambed, there is no stream/ground-water exchange.) For gaining 

stream reaches, as was the case for losing and neutral streams, 

a temperature gradient is created at the streambed surface 

because of convective heat transfer. As ground water discharges 

to the stream, however, the stream-temperature extremes are 

attenuated at shallow depths because of the heat capacity of the 

discharging ground water, such that the greater the ground-water 

discharge the greater the attenuation of temperature extremes 

and the greater the lag in temperature extremes in the sediments 

(for example, Silliman and Booth, 1993).

These heat-transfer processes also have important ramifications on stream-temperature patterns. Constantz (1998) 

examined streamflow and stream-temperature patterns on the 

Truckee River, California, and its tributaries to demonstrate 

the use of stream-temperature analysis to determine spatial 

and temporal patterns of exchange in selected reaches. For 

example, results in this work showed that stream-temperature 

patterns could be used to demonstrate that the main-stem 

Truckee River received significant water from bank storage 

in response to upstream dam releases, whereas the tributary 

directly downstream from the dam possessed inadequate bank 

storage to influence post-release stream-temperature patterns 

(see Constantz, 1998, fig. 10).

Quantitative Analyses of Heat as a 

Ground-Water Tracer Near a Stream

Rorabaugh (1954) examined correlations between stream 

temperature and seepage patterns and proposed the measurement of temperature to quantify heat flow, and thus determine 

streambed seepage indirectly. He indicated that a ground-water 

model capable of quantifying heat and water fluxes appeared 

to be the appropriate tool. A physically based, quantitative 

analysis of heat and water transport through porous materials 

was introduced by Philip and deVries (1957). Their analysis 

resulted in a comprehensive mathematical description of the 

coupled process of liquid and vapor water transport simultaneous with the transfer of heat in the solid, liquid, and vapor 

phases of unsaturated porous material. Application of their 

analysis has demonstrated that the transport of heat and water 

in the vapor phase often is important in unsaturated soils, 

and generally dominates in dry environments (for example, 

Scanlon and Milly, 1994). As the degree of water saturation increases in sediments, heat transport in the vapor phase 

abruptly declines as the gas phase becomes discontinuous and 

then vanishes as sediments approach saturation (for example, 

Stonestrom and Rubin, 1989). As a result, the comprehensive approach developed by Philip and deVries (1957) is 

unnecessary for analysis of heat and water fluxes in material 

that is sufficiently saturated to inhibit macroscopic gas flow. 

Streambed sediments beneath wetted channels are sufficiently 

saturated to ignore macroscopic vapor transport.

Suzuki (1960) and Stallman (1963, 1965) were able to 

use a single-phase approach to predict water fluxes through 

saturated sediments, based on measured ground-water 

temperatures. Their work formed the basis for examination of 

flow in environments ranging from deep ground-water systems 

(Bredehoeft and Popadopulos, 1965) to humid hillslopes 

(Cartwright, 1974). Stallman (1963) presented a general 

equation describing the simultaneous flow of heat and fluid in 

the earth. He indicated that ground-water temperatures could 

be used to determine the direction and rate of water movement. He also indicated that temperatures in combination 

with hydraulic gradients could be used to estimate sediment 
Analysis of Temperature Gradients to Determine Stream Exchanges with Ground Water 119

hydraulic conductivity. Stallman’s equation for the simultaneous 

transfer of heat and water through saturated sediments for the 

one-dimensional case of vertical flow (z direction) is as follows:

K T

z

q

T

z

T

t t

u

u 
 uu  uu

2

2 Cw Cs , (1)

where

Kt is the thermal conductivity of the bulk 

streambed sediments in W/(m °C);

T is temperature in degrees Celsius;

q is the liquid water flux through the sediments 

in meters per second;

Cw and Cs are the volumetric heat capacity of water 

and the bulk sediment in J/(m3 °C), 

respectively;

and

t is time in seconds.

The value of q is controlled by the Darcy equation as the 

product of the hydraulic conductivity, K, and the total head 

gradient, h. When q is zero, the equation reduces to the Fourier 

equation for the transfer of heat by conduction, and when q is 

large, advection dominates the transfer of heat, as well as the 

change of temperature throughout the porous material.

Thermal parameters can be estimated, given some knowledge of streambed materials. The heat capacity of the sediments can be estimated by the following:

Cs = ƒs(cs s) + ƒw(cw w) + ƒa(ca a), (2)

where f

s

, f

w, and fa

 are the volumetric fractions of the sediment, 

water, and air, respectively; cs

, cw, and ca are specific heats in 

J/(kg °C) of the sediment water and air, respectively; and s

, 

w, and a

 are the densities in kg/m3 of the sediment, water, 

and air, respectively. The product of the specific heat capacity and the density is the volumetric heat capacity, which is in 

the range of 0.8 × 106

, 4.2 × 106, and 0.001 × 106 J/(m3 °C) for 

sediments, water and air, respectively (de Vries, 1963).

An alternative approach to describe simultaneous heat 

and water transport through sediments has been to use an 

energy transport approach via the convective-dispersion equation (Kipp, 1987). These coupled heat and water-flow equations are included here as equations 3, 4, and 5.

∂ [ ] + −

∂ = ∇⋅ ∇ +∇⋅ ∇

−∇⋅ +

θ φ θ θ

θ

C CT

t

Kt T C D T

C Tq QC T

w s

w h

w w

( ) ( )

,

1

(3)

where

	 	 is percent volumetric water content;

 is sediment porosity, dimensionless;

Dh is thermomechanical dispersion tensor, 

in square meters per second;

q is the water flux, in meters per second,

and

Q is rate of fluid source, in seconds.

The left side of the equation represents the change in energy 

stored in a volume over time. The first term on the right side 

describes the energy transport by heat conduction. The second 

term on the right side accounts for thermomechanical dispersion. The third term on the right side represents advective heat 

transport, and the final term on the right side represents heat 

sources or sinks to mass movement into or out of the volume. 

The familiar water-flow equation is as follows:

C x h x t

t

( , ) k x h x t ( , ) Y Y [ ( , ) ( , )] u

u    , (4)

where

C(, x)	 is specific moisture capacity, which is the 

slope of the water-retention curve;

 is the water pressure, in meters;

h is the total head, in meters;

x is length, in meters;

and

t is time in seconds (Buckingham, 1907; 

Richards, 1931).

The thermomechanical dispersion tensor is defined as 

(Healy, 1990):

D v

v v

v h T i j

l t i j   
 A D A A

,

( ) , (5)

where αl and αt are longitudinal and transverse dispersivities, 

respectively, in m; δi,j is the Kronecker delta function; νi and

νj are the ith and jth component of the velocity vector, respectively, in meters per second.

Sediment thermal conductivity, Kt

, varies with texture and 

degree of saturation; for the typical case of saturated sediment 

in a general textural class, however, the uncertainty is greatly 

reduced. For example, the streambed Kt

 for a sand channel 

is likely to range only from 1.0 to 2.0 W/(m °C), so that the 

value of Kt

 can be estimated as 1.5 W/(m °C) ± 0.5 W/(m °C) 

(van Duin, 1963).

After the thermal parameters are assigned, q is estimated 

via an appropriate heat and mass-transport simulation model 

(discussed in detail below). Generally, hydraulic conductivity 

cannot be estimated using this procedure. As opposed to Kt

, 

hydraulic conductivity can vary over several orders of magnitude. Even for saturated conditions, the hydraulic conductivity 

of sand-textured material can vary from values of 10–2 down to 

10–6 m/s (Freeze and Cherry, p. 29, 1979). For a given sandtextured material, as saturation decreased, values of hydraulic 

conductivity measured in the laboratory ranged from 10–5 meters 

per second down to 10–10 (for example, Constantz, 1982). Consequently, hydraulic conductivity is not isolated from q without 

an accurate measurement of the hydraulic gradient. For many 

studies, the goal is to develop estimates of q, so that temperature 

measurements applied to equation 1 or equation 2 have proved 

useful in determining the rate of water movement through 

a region of interest. In some studies (as discussed below), 

hydraulic gradients are determined on the basis of piezometer 

measurements, so that values of hydraulic conductivity also are 

estimated from sediment-temperature patterns.
120 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Using reasonable boundary conditions and thermal and 

hydraulic parameters, a heat- and water-transport simulation 

code is run to predict temperature patterns in stream sediments. For the present application, predicted temperature patterns are matched to measured data using an inverse-modeling 

approach. Specifically, hydraulic information, such as stream 

stage, are determined, temperatures are monitored in the 

stream and streambed, and predicted temperatures then are 

compared with measured temperatures by using trial-and-error 

methods or a parameter-estimation code.

Temperature Instrumentation

Background

Measurement of temperature gradients in the sediments 

is required to estimate the rate of heat transfer through the 

streambed. Measurement of temperature over time at two or 

more depths within the stream/ground-water system is the 

minimum temperature data needed to estimate heat and water 

fluxes in the domain bounded by the temperature measurements. When it is desirable to separate water fluxes into 

hydraulic conductivity and the hydraulic-gradient components, 

measurements of hydraulic gradients are required in addition to temperature gradients. Accuracy in estimating thermal 

parameters sometimes is improved through laboratory analysis 

of sediment samples, especially for variables in equation 2 and 

equation 4; however, the spatial variability of textures in fluvial environments often diminishes the effectiveness of coring 

efforts, such that an estimate based on the bulk textural class 

over the domain of interest may be a more prudent approach. 

Operationally, measurements of temperature in the stream 

environment involves logistical issues, which generally do not 

occur in forest or agriculture settings (for example, Jaynes, 

1990). In the stream environment, fluvial processes create 

installation challenges that often have to be overcome on a 

site-by-site basis. Some streams are wide and shallow with 

a mantle of boulders, whereas other streams are deep with 

steep banks. Furthermore, damage to or loss of temperature 

equipment, because of high streamflows, is an issue unique 

to streams. Equipment selection and installation methods are 

usually site specific, though two common requirements are 

equipment that is sufficiently durable in high flows and an 

installation procedure that avoids preferential flow of pore 

water along the length of the equipment embedded in the 

streambed. Often, the manner in which temperature is measured may differ for ephemeral channels as compared with 

perennial channels.

Figure 1 provides a qualitative, pictorial description of 

the thermal and hydraulic responses to the four possible states 

of a streambed—a gaining stream, a losing stream, a dry 

ephemeral channel, and an ephemeral channel with water. The 

purpose of this figure is to provide graphical depictions of conditions relevant to the installation of monitoring equipment. 

Within each panel of the figure, a hydrograph is depicted 

on the right, while a pair of thermographs, representing the 

diurnal pattern in the stream and streambed temperatures, are 

depicted on the left. For the case of a gaining stream (fig. 1A), 

the hydraulic gradient is upward as indicated by the positive 

water pressure in the observation well relative to the stream 

stage. The stream is shown with a large diurnal variation in 

water temperature, but the sediment temperature has only a 

slight diurnal variation. The diurnal variation in the sediment 

is due to the inflow of ground water to the stream, which is 

generally of constant temperature on the diurnal time scale. 

Any variation in sediment temperature is a result of a change 

in the balance between downward conductive transport of 

heat and upward advective transport of heat. Thus, for a high 

inflow of ground water, the sediment temperature will have no 

diurnal variations, whereas for a slight inflow of ground water, 

the sediment will have a small diurnal variation in temperature (which will be increasingly damped with depth). Consequently, shallow installation of temperature equipment (in the 

observation well or directly in the streambed) is desired for a 

gaining stream reach in order to detect significant temperature 

variations. For the case of a losing stream (fig. 1B), the downward hydraulic gradient transports heat from the stream into 

the sediments. The combined conductive and advective heat 

transport can result in large diurnal fluctuations in sediment 

temperature. Furthermore, because ground water is not flowing into the stream, stream-temperature variations generally 

are larger than those for gaining streams (Constantz, 1998). 

Consequently, deeper installation of temperature equipment 

(in the observation well or directly in the streambed) may 

be in order for losing streams. For a dry streambed (fig. 1C), 

pore-water pressures are negative relative to atmospheric 

pressure, and, thus, are not measurable in a observation well. 

The streambed may have extremely high variations in diurnal 

temperature because of radiative heat transfer; however, the 

combined effects of low Kt

 values and no advective heat transport results in negligible diurnal variations in sediment temperatures below the shallowest (for example, 10 centimeters) 

streambed depths. For ephemeral stream channels (fig. 1D), a 

dynamic temperature pattern exists at the initiation of streamflow. Again, the observation well remains empty because of 

negative pore-water pressures until mounding of the water 

table results in water entry into the well. For the ephemeral 

case, convective, conductive, and advective heat transport all 

contribute to the rapid responses in the streambed surface and 

underlying sediments, as seen in the abrupt response of the 

streambed thermograph.

Direct Versus Indirect Measurements

Water and sediment temperatures can be measured directly 

by inserting a temperature probe (that is, thermistor wire, 

thermocouple wire, or platinum resistance thermometer wire) 

into the medium of interest, or indirectly by inserting the probe 

to a depth of interest in an observation well. In either case, the 

selected temperature probe is connected to a data logger. Within 
Analysis of Temperature Gradients to Determine Stream Exchanges with Ground Water 121

observation wells, temperature can be monitored with temperature-logging equipment on a specific schedule such as hourly, 

daily, or monthly (see Lapham, 1988), or alternatively, temperature can be continuously monitored at fixed locations within 

the observation well, using either a series of temperature probes 

at specific depths, or a series of single-channel, submersible 

microdata loggers tethered at several locations in the observation 

well (see Bartolino and Niswonger, 1999). There has been some 

concern about heat conduction down the observation well, and 

Lapham (1988) suggested that at least the first meter below the 

streambed may be influenced by the upper boundary. Another 

concern has been the development of a convection cell in observation wells that would redistribute heat within the well. For a typical shallow observation well with a 0.05-meter-diameter opening, 

Samuels (1968) calculated that a convection cell 0.5 meter in 

length could be established at the top of the water column during 

periods of large upward thermal gradients (for example, during 

winter). Samuels demonstrated that for large upward thermal 

gradients, the temperature in the upper water column could be 

erroneously high by 0.5 °C. These two complications indicate that 

measurements in the shallow water column within a observation 

well may less accurately represent the temperature in the surrounding sediments than values obtained deeper in the well-water 

column. These complications will be addressed in the final section of this chapter.

Observation wells generally are air filled in ephemeral stream channels, resulting in poor estimates of diurnal 

temperature variations due to the extremely low thermal 

conductivity of the air cavity. Thus, streambed temperatures 

need to be taken directly in the sediment rather than in the 

observation wells for ephemeral channels. Vertical arrays of 

thermocouples or thermistors (or temperature nests) have been 

successfully installed directly into flowing ephemeral channels (Thomas and others, 2000). Thermistor or thermocouple 

wires are inserted down a drill hole, and as the drill stem is 

withdrawn, saturated sediment collapses into the hole, thus 

inhibiting preferential flow. Wires then are run horizontally, 

either bare or in conduit, to a data-acquisition system. For 

dry ephemeral channels, thermistor or thermocouple wires 

are installed into the streambed in a similar fashion as for the 

flowing case; however, backfilling with either native materials 

or with diatomaceous earth is necessary to inhibit preferential 

flow next to the wires. Instrumentation also can be installed 

horizontally from a trench excavated along the bank (see 

Ronan and others, 1998). Recently, single-channel, submersible microdata loggers have been successfully installed in dry 

streambeds using a drill rig and backfill (Bailey and others, 

2000). For a detailed description of numerous options for 

using and monitoring of sediment temperature, see Stonestrom 

and Constantz (2003).

EPHEMERAL STREAM

Time

Temperature

Time

Streamflow 0

Stream Gage

DRY STREAMBED

Time

Time

Temperature

Streamflow 0

LOSING STREAM

Time

Temperature

Time

Streamflow

Stream Gage

GAINING STREAM

Time

Time

Temperature

Streamflow

Stream Gage

1 meter 1 meter

A

B

C

D

1 meter 1meter

Stream Gage

Piezometer

Piezometer

Piezometer

Piezometer

Figure 1. A qualitative description of thermal and hydraulic 

responses to four possible states of a streambed: A, gaining 

stream, B, losing stream, C, dry streambed, and D, ephemeral 

stream. Thermographs and hydrographs are displayed in the 

upper left and right corners, respectively.
122 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Methods to Analyze Streambed 

Temperatures

Several researchers have developed simplifying assumptions 

for specific hydrological conditions that preclude the necessity 

of using a heat- and ground-water-transport simulation model. A 

simplistic, first-approximation approach was developed for the 

case in which pore-water velocities are sufficiently high such that 

heat transport by conduction is negligible compared with heat 

transport by advection. This case is typical during flow events 

in many ephemeral streambeds (see fig. 1D), and common in 

perennial stream channels where a dense clay layer is absent. For 

those cases in which conduction is small compared to advection, 

pore-water velocity, v, is approximated by:

v V Cs

Cw  T

1

Q

, (6)

where

VT is the vertical velocity of the temperature 

peak (the “wave” or “front”) down into 

the streambed sediments.

This simplification has been shown to work well in a laboratory column (Taniguchi and Sharma, 1990) and in artificial 

recharge basin studies (Cartwright, 1974). The flux, q, can 

be determined from the product of v and  . The value of 

can be approximated by the porosity of the streambed sediments, although Constantz and others (1988) determined that 

a value of 0.9 may be more typical for the initial stages of 

ponded infiltration. Constantz and Thomas (1996, 1997) have 

successfully applied this simplification at Tijeras Arroyo, 

New Mexico, by monitoring temperatures between the surface 

and a depth of about 3 meters during ephemeral streamflow events. Stewart (2003) examined the error in using this 

simplistic approach compared to a complete description of 

conductive and convective heat transport. Stewart reported 

that the use of equation 6 could overestimate water fluxes by 

30 percent for cases in which heat conduction is a significant 

component of the total heat flux within streambeds.

Silliman and others (Silliman and Booth, 1993; Silliman 

and others, 1995) used time-series analysis of stream and 

sediment temperature patterns in Indiana to identify losing 

reaches. In a similar fashion to Suzuki (1960) working in rice 

fields, Silliman and others used a one-dimensional solution to 

equation 1, with an assumed sinusoidal temperature pattern for 

upper boundary condition. Silliman and Booth (1995) examined the range of the Peclet number (a measure of advective to 

conductive transport) for which a solution should be applicable (see Silliman and Booth, 1995, p. 106, for the specific 

values for Peclet parameters that they chose for a streambed 

environment). They concluded that for Peclet numbers of less 

than 2 × 10–4, which represent a flux of 8 × 10–8 meters per 

second, the advective component of the solution is negligible. 

Thus, this approach may not be useful for the very low water 

fluxes typical of streambed environments with extensive claytextured streambeds and (or) very low hydraulic gradients.

Ronan and others (1998) used the heat- and water-transport 

simulation code VS2DH (Healy and Ronan, 1996) to model the 

ground-water-flow pattern below Vicee Canyon, Nevada. The 

ephemeral stream channel within Vicee Canyon meanders over 

an alluvial fan on the east side of the Carson Range of western Nevada. Along the fan, temperature was monitored in the 

stream channel and streambed using a 3-meter by 3-meter grid 

of 24 thermocouples at three locations. The two-dimensional 

simulation code was used in an inverse modeling approach to 

match simulated temperature against measured temperature 

to estimate heat and water fluxes into or out of the streambed 

vertically and horizontally. After calibration of the model during 

one season, simulation results were able to predict streamflow 

loss and streambed infiltration based only on temperature data. 

Their results used values for dispersivity of about 0.01 meter, 

indicating that thermal dispersion does not appear to be significant in this type of environment for this length scale (3 meters). 

Incorporating two-dimensional temperature patterns as input 

into the model was useful in demonstrating the asymmetrical 

pattern of substream ground-water flow as a result of down-canyon ground-water flow as the stream meandered across the fan.

The use of heat as a tracer to examine stream/groundwater exchanges has not been limited to shallow investigations. Deeper monitoring of substream temperatures has been 

done by Lapham (1989) and Bartolino and Niswonger (1999) 

to estimate annual patterns of stream/ground-water exchanges, 

where temperatures were periodically logged in observation 

wells as deep as 50 meters below the streambed. Long-term 

temperature monitoring provides a series of temperature 

profiles that can be useful in characterizing streambed fluxes. 

Figure 2 shows hypothetical streambed-temperature profiles 

for a losing stream (downward water flux) compared with a 

gaining stream (upward water flux) over either a year or a day. 

The temperature profiles for the annual (or daily) extremes 

Figure 2. The streambed temperature profiles (temperature 

envelopes) for a losing stream (downward water flux) compared 

to a gaining stream (upward water flux) for the annual example 

and the diurnal example. Increasing Temperature

Stream

Z

Annual (or Diurnal) Streambed-Temperature Profile

Z = 10 meters (or 0.1 meter)

Upward flux

Downward flux

Winter

(afternoon)

(afternoon)

(dawn)

(dawn)

Winter

Summer

Summer
Analysis of Temperature Gradients to Determine Stream Exchanges with Ground Water 123

forms a “temperature envelope” for a particular site, within 

which all other temperature profiles reside. On an annual 

scale, the January and July temperature profiles typically 

form an envelope in which other monthly temperature profiles 

reside. When ground water is discharging to the stream, the 

annual envelope is collapsed toward the streambed surface, 

and when the stream is rapidly losing water to the sediments, 

the envelope extends to great depths. This is true on a daily 

time scale as well, with the dawn and afternoon temperature 

profiles forming the daily envelope, in which all other hourly 

temperature profiles reside. A salient difference between the 

annual and daily temperature envelopes is the depth scale. See 

Lapham (1989) for a series of annual and daily example temperature envelopes from streams in the eastern United States.

Figure 3 depicts the effect of changing values of hydraulic conductivity on temperature profiles, based on results for 

the Rio Grande at Albuquerque, New Mexico (Bartolino and 

Niswonger, 1999). The figure compares the optimal fit value 

for hydraulic conductivity (6.7 × 10–6 meters per second) with 

an order of magnitude increase in hydraulic conductivity, an 

order of magnitude decrease in hydraulic conductivity, and the 

optimal hydraulic conductivity with a reversed hydraulic gradient. The large sensitivity of streambed temperature to different 

hydraulic conditions is clearly apparent. To a lesser extent, 

simulated flux estimates also are sensitive to uncertainty in thermal parameters. Niswonger and Rupp (2000) used Monte Carlo 

analysis to examine the relative importance of errors in estimating temperature, Kt

, and Cs to the resulting simulated water 

fluxes for Trout Creek, Nevada. When isolating thermal properties, they determined that for the expected mean and standard 

deviation in thermal parameters, resulting VS2DH simulated 

water fluxes were most sensitive to uncertainties in sediment 

temperature and least sensitive to uncertainties in Kt

. In general, 

predicted fluxes were highly sensitive to variations in hydraulic 

properties and slightly sensitive to variations in thermal properties for the range of properties reported for sediments.

Example Sites

Study results from two sites are summarized below to 

provide example applications of the use of heat as a natural 

tracer of ground-water movement near streams. These sites 

were chosen because: (1) they are characterized by distinctly 

different seasonal streamflow patterns; and (2) at the first site, 

a direct temperature monitoring technique was used, whereas 

at the second site, an indirect monitoring technique was used. 

Both sites were losing stream reaches during the study period; 

however, the techniques described work equally as well on 

gaining stream reaches. For an example of direct and indirect temperature measurements used in gaining reaches to 

estimate upward water fluxes, see Silliman and Booth (1993) 

for direct temperature measurements made in sediments, and 

Lapham (1988) for indirect temperature measurements made 

in observation wells.

Bear Canyon, New Mexico

Bear Canyon is on the eastern edge of Albuquerque, 

New Mexico. The small ephemeral stream within the canyon 

is a representative example of more than 100 similar streams 

that drain from the western flanks of the Sandia and Manzano 

Mountains into the Middle Rio Grande Basin. The flows in these 

ephemeral streams have the common characteristics of being 

bedrock-controlled in their upper gaining reaches, and alluviumcontrolled in their lower losing reaches. The streamflow and 

stream-loss patterns of these stream channels are poorly documented, but their cumulative streambed infiltration might contribute significantly to potential recharge to the basin.

The use of streambed-temperature data was included 

in a suite of monitoring methods and field-reconnaissance 

procedures intended to estimate streamflow loss and potential 

recharge along a reach of Bear Canyon. This reach extends 

from the exposed bedrock at the mountain-front downslope in 

a westward direction for about 3 kilometers, at which point the 

stream channel has been modified as a result of urbanization. 

The stream is perennial east of the bedrock exposure at the 

mountain front, and flows rarely extend more than 1 kilometer 

from the mountain front, though summer monsoons occasionally induce streamflow to the confluence with the Rio Grande, 

approximately 20 kilometers to the west of the mountain front.

Two temperature-monitoring methods were used within 

the stream channel of Bear Canyon from 1996 through 1999. 

Streambed surface temperatures were monitored at sites between 

TEMPERATURE, IN DEGREES CELSIUS

DEPTH, IN METERS

Data

Optimal

K=1 order lower

K=1 order higher

Reverse gradient

8 10 12 14 16 18 20 22 24

3

5

7

9

11

13

15

Figure 3. The simulated temperature profile below the 

Rio Grande in central New Mexico for an optimized value of K

(hydraulic conductivity), compared to a value of K one order 

of magnitude greater or less than the optimal value, and the 

temperature profile with an optimal value of K, but with an upward 

value of H (heat) to simulate a gaining stream, based on measured 

results in Bartolino and Niswonger (1999).
124 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

the mountain front and the modified reach of the channel, 3 

kilometers to the west of the mountain front. Surface-temperature 

patterns were analyzed as part of the characterization of the 

spatial and temporal pattern of streamflow in Bear Canyon. 

Procedures and results for the surface-temperature measurements 

are described in detail in Constantz and others (2001). Vertical 

temperature patterns were monitored by using a series of thermocouple wires installed at depths between the streambed surface 

and about 3 meters below the channel to create a temperature 

nest in a fashion similar to that described in Thomas and others 

(2000). Temperature nests were installed at two locations in the 

middle reach of the Bear Canyon study site, where ephemeral 

streamflows were expected to be present for extended periods. 

After backfilling installation holes, the completed temperature nests monitored temperature at 0.40, 0.60, 1.10, 2.10, and 

3.10 meters below the streambed surface. Temperatures were 

monitored at 15-minute intervals via a data logger in an enclosure 

near the stream channel until September 1999.

Seasonal snowmelt resulted in a gradual progression 

of the downstream limit of flow down-channel over several 

months in the spring, followed by a retreat up-channel in early 

summer. Flashy, summer monsoon streamflow occurred in 

some, but not all years. Details of the late stages of spring 

streamflow at one temperature nest in the channel are shown in 

figure 4. As expected, the greatest diurnal temperature variations are those at a depth of 0.40 meter, and the smallest diurnal temperature variations are those at a depth of 3.10 meters. 

The abrupt retreat of streamflow upstream in Bear Canyon 

also is clearly detectable. As streamflow retreated up-channel 

from this site on June 5, 1999, the abrupt transition from 

advection-dominated heat transport to conduction-dominated 

heat transport is quite distinct. Reduced magnitudes in diurnal 

variations in streambed temperature result from the loss of 

advective heat transport with the cessation of streamflow into 

the streambed.

The streambed-temperature profiles generated at temperature nests during annual spring streamflow were used as input 

in a fitting procedure that compared measured temperatures 

to simulated temperature using VS2DH in order to estimate 

streambed infiltration rates. A commercially available optimization program was used to determine the streambed-sediment 

hydraulic conductivity from the best fit between the simulated 

streambed temperatures and measured sediment temperatures. 

Figure 5 shows sediment temperatures during June 1997 at 

four depths below the streambed at a vertical temperature site 

approximately 275 meters west of the mountain front. The figure also shows the simulated best fit at 0.60 meter using an optimization program. The measured streambed temperatures were 

applied as the upper thermal boundary condition, and measured 

hydraulic gradients and stream stage were used for hydraulicboundary conditions. Saturated conditions existed below the 

stream channel as determined by measuring water levels with 

piezometers set in the streambed. An optimized seepage rate 

of 0.75 meter per day resulted in the fit for a depth of 0.6 meter 

as shown in figure 5 (fits for 0.4 and 1.1 meter depth were 

comparable but not shown in the figure for clarity of individual 

thermographs). Optimized simulations for the duration of spring 

streamflow for this site indicated an average vertical streambed seepage rate of 0.77 meter per day. The consistency in the 

estimated seepage rate over the duration of the spring season 

indicates that neither the hydraulic conditions nor the streambed sediments in Bear Canyon were transient. This magnitude 

of streambed infiltration persisted until retreat of streamflow 

up-canyon, at which time water fluxes rapidly declined during 

drainage of the streambed.

6

8

10

12

14

16

18

20

TEMPERATURE,

IN DEGREES CELSIUS

0.4 meter

0.6 meter

0.6 meter simulated

1.1 meters

2.1 meters

6/9 10:00 6/9 22:00 6/10 10:00 6/10 22:00 6/11 10:00 6/11 22:00 6/12 10:00 6/12 22:00

EXPLANATION

0

10

20

30

TEMPERATURE,

IN DEGREES CELSIUS

0.4 meter

0.6 meter

1.1 meters

2.1 meters

3.1 meters

Streamflow

5/6/1999 5/11/1999 5/16/1999 5/21/1999 5/26/1999 5/31/1999 6/5/1999 6/10/1999 6/15/1999 Dry streambed

EXPLANATION

Figure 4. The streambed-temperature patterns resulting from late stages of continuous spring streamflows progressing to abrupt 

cessation of streamflow, approximately 275 meters west of the mountain front in Bear Canyon, New Mexico, during June 1999.

Figure 5. The streambed-temperature patterns compared to optimized (simulated) sediment temperatures at a depth of 0.6 meter, 

approximately 275 meters west of the mountain front in Bear Canyon, New Mexico, during June 1997.
Analysis of Temperature Gradients to Determine Stream Exchanges with Ground Water 125

Santa Clara River, California

The Santa Clara River is in southern California, flowing 

from the San Gabriel Mountains approximately 200 kilometers 

to the Pacific Ocean. In the upper reaches, the gradient is steep, 

and the stream generally flows over bedrock with a steady gain 

of ground water. In the middle reaches, the stream flows over a 

wide sandy channel, resulting in large diurnal stream-temperature 

fluctuations, as well as substantial potential for stream/groundwater interaction. A 17-kilometer study section was defined in the 

middle reaches of the river, and a variety of hydrological properties were monitored using a range of surface- and ground-water 

instrumentation. As part of this larger study, an observation well 

was installed in the deepest section of a losing reach (referred to 

as SCR5) in October 1999. The observation well was approximately 4 meters in length with a 0.08-meter internal diameter. The 

observation well was driven approximately 2.5 meters into the 

streambed, at which time the drive point was driven from the bottom of the observation well. Temperature between the streambed 

and the bottom of each observation well was monitored by tethering one single-channel, submersible temperature microdata logger 

outside the observation well to monitor stream temperature and 

by tethering three microdata loggers inside the observation well at 

about 0.6, 1.2, and 2.4 meters below the streambed. The VS2DH 

simulation code was used to compare one-dimensional simulated temperatures with measured temperatures with a best-fit 

trial and error match, in order to estimate streambed-percolation 

rates. Temperature at depth for SCR5 during October 1999 varied 

during periods in which the stream did not flow and when the 

stream did flow at this observation-well site. Simulation results 

matched measured data very well during streamflow, but resulted 

in a poor match during the intermediate no-flow period at all 

depths monitored (fig. 6). The poor match during this period is 

expected because of water drainage from inside the observation 

well. Thus, microdata loggers suspended in the air-filled interior 

of the observation well were thermally isolated from the adjacent 

sediment during the no-flow period. Once streamflow returned 

to this location in the stream, the microdata loggers again were 

submerged and able to effectively monitor sediment temperatures. 

Consequently, the simulated results probably more correctly 

matched the sediment temperature during the no-flow period than 

did the microdata loggers. Direct burial of temperature equipment 

in the streambed sediments would have avoided the difficulty in 

monitoring temperature during this period without streamflow. 

The best-fit simulated temperatures shown in figure 6 resulted 

in a streambed infiltration rate of 1.8 meters per day, and based 

on the measured hydraulic gradient in the observation well of 

0.41 meter per meter, the derived hydraulic conductivity was 

5.1 × 10–5 meters per second.

Temperatures logged beneath the streambed at 0.3 meter 

varied in comparison to temperature logged inside the piezometer at the same depth as a function of presence or absence of 

flowing water in the stream (fig. 7). The agreement between 

the streambed and piezometer temperatures is excellent 

when streamflow is present and, as expected, agreement is 

poor during the no-flow period because of drainage of the 

piezometer and resultant thermal isolation of the microdata 

logger. The period of excellent agreement between the measured temperatures probably is a result of the strong advective 

transport of heat at SCR5, such that conduction of heat down 

the piezometer is small relative to the total transport of heat. 

Further research is needed to determine the depth of influence 

of piezometer heat conduction for stream sites where heat 

conduction is the dominant heat-transport process with the 

streambed. Realistically, in environments where conduction is 

the dominant mechanism of heat transport, piezometer design 

needs to incorporate features that inhibit heat transport vertically along the piezometer while still allowing heat transport 

horizontally from the sediments to the piezometer. Though 

the results depicted in figure 7 show good agreement between 

temperatures, the flux range for good agreement warrants 

further examination.

 Depth of 0.61 meter

10

12

14

16

18

20

22

24

26

28

TEMPERATURE,

IN DEGREES CELSIUS

10/7/1999 10/9/1999 10/11/1999 10/13/1999 10/15/1999 10/17/1999 10/19/1999 10/21/1999 10/23/1999

EXPLANATION

Dry streambed

Streamflow

Measured data

Simulated temperatures

Figure 6. The measured sediment temperatures compared with simulated streambed temperatures at a depth of 

0.6 meter below the streambed surface at observation site SCR5 on the Santa Clara River, California, during October 1999. 

(Note that streamflow ceased and resumed at the site in the middle of the period of record, as indicated by the horizontal 

lines at the bottom of the graph.)
126 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Summary

In summary, the measurement and analysis of temperature gradients in streambed sediments provide qualitative 

patterns and quantitative estimates of rates and direction of 

water movement through sediments. Both the temporal range, 

and spatial scale, over which temperature gradients have 

been analyzed to use heat as a natural tracer of ground-water 

movement near streams has been greatly extended by numerous recent case studies. Currently, research is ongoing in the 

areas such as thermal and hydraulic parameter optimization 

and time-series analysis of temperature gradients to expand 

the use of heat as a natural tracer in more complex, highly 

heterogeneous environments.

Recent improvements in acquisition of sediment temperatures and in simulation modeling of heat- and groundwater transport are leading to widespread implementation of 

methods in which heat is used to trace ground-water fluxes 

near streams. This chapter provides a brief historical review of 

the use of heat as a tracer of shallow ground-water movement, 

and details current theory used to estimate stream/groundwater exchanges. Techniques for installation and monitoring 

of temperature and stage equipment are discussed in detail for 

a range of hydrological environments. These techniques are 

divided into either direct temperature measurements in streams 

and sediments or indirect measurements in observation wells. 

Methods of analysis of acquired temperature measurements 

include analytical solution, heat- and water-transport simulation models, and simple heat-pulse arrival-time procedures. 

Temperature and derived-flux results are presented for field 

sites in Bear Canyon, New Mexico, and the Santa Clara River, 

California. Direct monitoring of temperatures in the sediments below Bear Canyon resulted in estimates of streambed 

infiltration of 0.75 meter per day, whereas indirect monitoring of sediment temperature using observation wells installed 

in the Santa Clara River, resulted in streambed-infiltration 

rates of 1.8 meters per day. The accuracy of measurements 

within piezometers was confirmed by comparing sediment 

temperatures acquired directly in sediments with temperatures 

acquired in a piezometer at the same depth.

28

26

24

22

20

18

16

14

12

10

10/8/1999 10/10/1999 10/12/1999 10/14/1999 10/16/1999 10/18/1999 10/20/1999

TEMPERATURE,

IN DEGREES CELSIUS

EXPLANATION

In sediment at 0.3-meter depth

In piezometer, 0.3 meter below 

 streambed

Streamflow

Dry streambed

Figure 7. A comparison of streambed temperatures measured directly in the sediments and temperatures measured inside 

the observation well for observation site SCR5 at a depth of 0.3 meter below the streambed surface on the Santa Clara River, 

California, during October 1999. (Note that streamflow ceased and resumed at the site in the middle of the period of record.)

References

Bailey, M.A., Ferre, P.A., and Hoffmann, J.P., 2000, 

Numerical simulation of measured streambed-temperature 

profiles and soil hydraulic properties to quantify infiltration in an ephemeral stream, American Geophysical Union, 

2000 Fall meeting supplement, San Francisco, California, 

December 15–19, 2000: EOS, Transactions, American 

Geophysical Union, v. 81, no. 48, p. F501–F502.

Bartolino, J.R., and Niswonger, R.G., 1999, Numerical simulations of vertical ground-water flux of the Rio Grande from 

ground-water temperature profiles, central New Mexico: 

U.S. Geological Survey Water-Resources Investigations 

Report 99–4212, 34 p.

Bouyoucos, G., 1915, Effects of temperature on some of the 

most important physical processes in soils: East Lansing, 

Michigan State University, Michigan College of Agriculture 

Technical Bulletin 24, 63 p.

Bredehoeft, J.D., and Papadopulos, I.S., 1965, Rates of vertical groundwater movement estimated from Earth’s thermal 

profile: Water Resources Research., v. 1, no. 2, p. 325–328.

Buckingham, Edgar, 1907, Studies on the movement of soil 

moisture: U.S. Department of Agriculture, Bureau of Soils, 

Bulletin no. 38, 61 p.

Burow, K.R., Constantz, Jim, and Fujii, Roger, 2005, Heat as 

a tracer to examine dissolved organic carbon flux from a 

restored wetland: Ground Water v. 43, no. 4, p. 545–556. 

Cartwright, K., 1974, Tracing shallow ground water systems 

by soil temperature: Water Resources Research, v. 10, no. 4, 

p. 847–855.

Constantz, J.E., 1982, Temperature dependence of unsaturated 

hydraulic conductivity of two soils: Soil Science Society of 

America Journal, v. 46, no. 3, p. 466–470.
Analysis of Temperature Gradients to Determine Stream Exchanges with Ground Water 127

Constantz, J.E., 1998, Interaction between stream temperature, 

streamflow, and ground water exchanges in alpine streams: 

Water Resources Research, v. 34, no. 7, p. 1609–1616.

Constantz, J.E., Herkelrath, W.N., and Murphy, Fred, 1988, 

Air encapsulation during infiltration: Soil Science Society 

of America Journal, v. 52, p. 10–16.

Constantz, J.E., and Thomas, C.L., 1996, The use of streambed temperatures profiles to estimate depth, duration, 

and rate of percolation beneath arroyos: Water Resources 

Research, v. 32, p. 3597–3602.

Constantz, J.E., and Thomas, C.L., 1997, Streambed temperature profiles as indicators of percolation characteristics 

beneath arroyos in the Middle Rio Grande Basin, USA: 

Hydrological Processes, v. 11, p. 1621–1634.

Constantz, J.E., Stonestrom, D.A., Stewart, A.E., Niswonger, 

R.G., and Smith, T.R., 2001, Evaluating streamflow patterns 

along seasonal and ephemeral channels by monitoring diurnal variations in streambed temperature: Water Resources 

Research, v. 13, no. 2, p. 317–328.

de Vries, D.A., 1963, Thermal properties of soils, in van Wijk, 

W.R., ed., Physics of the plant environment: Amsterdam, 

North-Holland Publishing Company, p. 210–235.

Freeze, R.A., and Cherry, J.A.,1979, Ground water: Englewood Cliff, New Jersey, Prentice-Hall, 604 p.

Healy, R.W., 1990, Simulation of solute transport in variably 

saturated porous media with supplemental information on 

modification of the U.S. Geological Survey’s computer 

program VS2D: U.S. Geological Survey Water-Resources 

Investigations Report 90–4025, 125 p.

Healy, R.W., and Ronan, A.D., 1996, Documentation of 

computer program VS2DH for simulation of energy transport in variably saturated porous media—Modification of 

the U.S. Geological Survey’s computer program VS2DT: 

U.S. Geological Survey Water-Resources Investigation 

Report 96–4230, 36 p.

Jaynes, D.B., 1990, Temperature variations effects on field 

measured infiltration: Soil Science Society of America 

Journal, v. 54, no. 2, p. 305–312.

Kipp, K.L., 1987, HST3D—A computer code for simulation 

of heat and solute transport in three-dimensional groundwater systems: U.S. Geological Survey Water-Resources 

Investigations Report 86–4095, 517 p.

Lapham, W.W., 1988, Conductive and convective heat transfer 

near stream: Tucson, University of Arizona, Ph.D. dissertation, 315 p.

Lapham, W.W., 1989, Use of temperature profiles beneath 

streams to determine rates of vertical ground-water flow 

and vertical hydraulic conductivity: U.S. Geological Survey 

Water-Supply Paper 2337, 35 p.

Niswonger, R.G., and Rupp, J.L., 2000, Monte Carlo analysis 

of streambed seepage rates, in Wigington, P.J., and Beschta, 

R.C., eds., Riparian ecology and management in multi-land 

use watersheds: American Water Resources Association, 

p. 161–166.

Richards, L.A., 1931, Capillary conduction of liquids through 

porous mediums: Physics, v. 1, p. 318–333.

Ronan, A.D., Prudic, D.E., Thodal, C.E., and Constantz, Jim, 

1998, Field study and simulation of diurnal temperature 

effects on infiltration and variably saturated flow beneath an 

ephemeral stream: Water Resources Research, v. 34, no. 9, 

p. 2197–2153.

Phillip, J.R., and deVries, D.A., 1957, Moisture movement 

in porous materials under temperature gradients: Eos, 

Transactions, American Geophysical Union, v. 38, no. 2, 

p. 222–232.

Rorabaugh, M.I., 1954, Streambed percolation in development 

of water supplies: U.S. Geological Survey Ground Water 

Notes on Hydraulics, no. 25, 13 p.

Samuels, E.A., 1968, Convective flow and its effect on temperature logging in small-diameter wells: Geophysics, v. 33, 

no. 6, p. 1004–1012.

Scanlon, B.R., and Milly, P.C.D., 1994, Water and heat fluxes 

in desert soils 2—Numerical simulations: Water Resources 

Research, v. 30, p. 721–733.

Silliman, S.E., and Booth, D.F., 1993, Analysis of time-series 

measurements of sediment temperature for identification 

of gaining versus losing portions of Judy Creek, Indiana: 

Journal of Hydrology, v. 146, no. 1–4, p. 131–148.

Silliman, S.E., Ramirez, Jose, and McCabe, R.L., 1995, Quantifying downflow through creek sediments using temperature time series—One-dimensional solution incorporating 

measured surface temperature: Journal of Hydrology, v. 167

no. 1–4, p. 99–119.

Stallman, R.W., 1963, Methods of collecting and interpreting 

ground-water data: U.S. Geological Survey Water-Supply 

Paper 1544–H, p. 36–46.
128 Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water

Stallman, R.W., 1965, Steady one-dimensional fluid flow 

in a semi-infinite porous medium with sinusoidal surface 

temperature: Journal of Geophysical Research, v. 70, 

no. 12, p. 2821–2827.

Stewart, A.E., 2003, Temperature-based estimates of streamflow 

patterns and seepage losses in ephemeral channels: Stanford, 

California, Stanford University, Ph.D. dissertation, 248 p.

Stonestrom, D.A., and Constantz, J.E., eds., 2003, Heat as 

a tool for studying the movement of ground water near 

streams: U.S. Geological Survey Circular 1260, 96 p.

Stonestrom, D.A., and Rubin, Jacob, 1989, Air permeability and trapped-air content in two soils: Water Resources 

Research, v. 25, no. 9, p. 1959–1969.

Su, G.W., Japerse, James, Seymour, Donald, and Constantz, 

J.E., 2004, Estimation of hydraulic conductivity in an alluvial system using temperature: Ground Water, v. 42, no. 6, 

p. 890–901.

Suzuki, Seitaro, 1960, Percolation measurements based on 

heat flow through soil with special reference to paddy 

fields: Journal of Geophysical Research, v. 65, no. 9, 

p. 2883–2885.

Taniguchi, Makoto, and Sharma, M.L., 1990, Solute and heat 

transport experiments for estimating recharge: Journal of 

Hydrology, v. 119, no. 1, p. 57–69.

Thomas, C.L., Stewart, A.E., and Constantz, J.E., 2000, 

Determination of infiltration and percolation rates along a 

reach of the Santa Fe River near La Bajada, New Mexico: 

U.S. Geological Survey Water-Resources Investigations 

Report 2000–4141, 65 p.

van Duin, R.H.A., 1963, The influence of soil management 

on the temperature wave near the surface: Wageningen, 

the Netherlands, Wageningen Institute of Land and Water 

Management, Technical Bulletin no. 29, 21 p.

For more information concerning this publication, contact:

Office of Ground Water

U.S. Geological Survey

411 National Center

12201 Sunrise Valley Drive

Reston, Virginia 20192

(703) 648-5001

Or visit the Office of Ground Water Web site at:

http://water.usgs.gov/ogw/

This publication is available online at:

http://pubs.usgs.gov/usgspubs/tm4D2

Publishing support provided by:

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Manuscript approved for publication, September 2007

Edited by Chester Zenone and Carol Anderson

Graphics and layout by Joy Monson
Printed on recycled paper