NATIONAL WATER-QUALITY ASSESSMENT PROGRAM

Estimating Water Fluxes Across the Sediment–Water 

Interface in the Lower Merced River, California

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2007–5216
Front cover: Lower Merced River, looking upstream at instrumented transect 1 in the study area. The photograph was 

taken in July 2003 during normal low-flow conditions (photo by Peter Dileanis, U.S. Geological Survey, Sacramento, 

California).

Back cover: Photographs of U.S. Geological Survey scientist Celia Zamora measuring the volume (milliliters) of water 

collected by seepage meter collection bag on north bank of the lower Merced River in the study area (left) and measuring 

the distance between temperature loggers and attaching them to a weighted line for placement in monitoring wells on 

the north bank of the lower Merced River in the study area (photo by Peter Dileanis, U.S. Geological Survey, Sacramento, 

California).
Estimating Water Fluxes Across the 

Sediment–Water Interface in the Lower 

Merced River, California

By Celia Zamora

National Water-Quality Assessment Program

Scientific Investigations Report 2007–5216

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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reproduce any copyrighted materials contained within this report.

Suggested reference:

Zamora, Celia, 2008, Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, 

California: U.S. Geological Survey Scientific Investigations Report 2007–5216, 47 p. Available at 

http://pubs.usgs.gov/sir/2007/5216/
iii

FOREWORD

The U.S. Geological Survey (USGS) is committed to providing the Nation with credible scientific information that 

helps to enhance and protect the overall quality of life and that facilitates effective management of water, biological, energy, and mineral resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical 

to ensuring long-term availability of water that is safe for drinking and recreation and is suitable for industry, 

irrigation, and fish and wildlife. Population growth and increasing demands for water make the availability of that 

water, now measured in terms of quantity and quality, even more essential to the long-term sustainability of our 

communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support national, 

regional, State, and local information needs and decisions related to water-quality management and policy (http://

water.usgs.gov/nawqa). The NAWQA Program is designed to answer: What is the condition of our Nation’s 

streams and ground water? How are conditions changing over time? How do natural features and human activities affect the quality of streams and ground water, and where are those effects most pronounced? By combining 

information on water chemistry, physical characteristics, stream habitat, and aquatic life, the NAWQA Program 

aims to provide science-based insights for current and emerging water issues and priorities. From 1991-2001, the 

NAWQA Program completed interdisciplinary assessments and established a baseline understanding of waterquality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.

gov/nawqa/studyu.html). 

Multiple national and regional assessments are ongoing in the second decade (2001–2012) of the NAWQA 

Program as 42 of the 51 Study Units are reassessed. These assessments extend the findings in the Study Units by 

determining status and trends at sites that have been consistently monitored for more than a decade, and filling 

critical gaps in characterizing the quality of surface water and ground water. For example, increased emphasis has 

been placed on assessing the quality of source water and finished water associated with many of the Nation’s 

largest community water systems. During the second decade, NAWQA is addressing five national priority topics 

that build an understanding of how natural features and human activities affect water quality, and establish links 

between sources of contaminants, the transport of those contaminants through the hydrologic system, and the 

potential effects of contaminants on humans and aquatic ecosystems. Included are topics on the fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream ecosystems, 

effects of nutrient enrichment on aquatic ecosystems, and transport of contaminants to public-supply wells. These 

topical studies are conducted in those Study Units most affected by these issues; they comprise a set of multiStudy-Unit designs for systematic national assessment. In addition, national syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, selected trace elements, and aquatic ecology are continuing. 

The USGS aims to disseminate credible, timely, and relevant science information to address practical and effective 

water-resource management and strategies that protect and restore water quality. We hope this NAWQA publication will provide you with insights and information to meet your needs, and will foster increased citizen awareness 

and involvement in the protection and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all water-resource issues 

of interest. External coordination at all levels is critical for cost-effective management, regulation, and conservation of our Nation’s water resources. The NAWQA Program, therefore, depends on advice and information from 

other agencies—Federal, State, regional, interstate, Tribal, and local—as well as nongovernmental organizations, 

industry, academia, and other stakeholder groups. Your assistance and suggestions are greatly appreciated.

Robert M. Hirsch

Associate Director of Water
iv

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v

Contents

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

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

Background............................................................................................................................................2

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

Study Area..............................................................................................................................................2

Geology..........................................................................................................................................2

Climate............................................................................................................................................7

Surface-Water Hydrology ..........................................................................................................8

Ground-Water Hydrology ...........................................................................................................8

Seepage Measurements ..............................................................................................................................9

Review of Literature .............................................................................................................................9

Field Measurements...........................................................................................................................10

Field Methods.............................................................................................................................10

Field Results................................................................................................................................13

Laboratory Measurements................................................................................................................14

Laboratory Methods..................................................................................................................14

Laboratory Results.....................................................................................................................16

Estimates of Streambed Hydraulic Conductivity ....................................................................................22

Methods................................................................................................................................................22

Grain-Size Analysis....................................................................................................................22

Hazen Approximation................................................................................................................23

Slug Tests ....................................................................................................................................24

Results. ..................................................................................................................................................25

Estimating Seepage Using Heat as a Tracer...........................................................................................27

Review of Literature ...........................................................................................................................27

Sampling Design and Methodology.................................................................................................28

Results. ..................................................................................................................................................30

Total-Head Distributions ...........................................................................................................30

Temperature Profiles.................................................................................................................32

Flux Estimates from Heat- and Water-Flow Model Analyses.............................................33

Conclusions...................................................................................................................................................40

References....................................................................................................................................................40

Appendix........................................................................................................................................................45
vi

Figures

Figure 1. Map showing study area and locations of fixed transect 1 and transect 2 in the 

lower Merced Basin ........................................................................ 3

Figure 2. Map showing location of monitoring wells and monitoring equipment at fixed 

transects 1 and 2 in the lower Merced Basin .......................................... 4

Figure 3. Graph showing mean annual streamflow, Merced River near Stevinson, 

California, water years 1941–2005 ......................................................... 8

Figure 4. Seepage meter arrays at transects 1 and 2 ............................................. 11

Figure 5. Photograph showing seepage meters ................................................... 12

Figure 6. Photograph showing field deployment of paired seepage meters..................... 12

Figure 7. Photograph showing scouring of streambed around seepage meter typically 

encountered 48 hours after deployment ................................................ 15

Figure 8. Graphs showing measured vertical flux rates over consecutive 24-hour 

measurement periods for seepage meter pairs A-1 and B-2........................... 15

Figure 9. Graphs showing measured vertical flux rates over consecutive 24-hour 

measurement periods for seepage meters pairs C-3 and D-4 ........................ 16

Figure 10. Graphs showing measured vertical flux rates over consecutive 24-hour 

measurement periods for seepage meter pairs E-5 and F-6 ........................... 17

Figure 11. Graph showing laboratory test tank setup used for testing of different types of 

collection bags attached to seepage meters .......................................... 18

Figure 12. Photograph showing seepage meter collection bag types ........................... 18

Figure 13. Graph showing boxplots of relative percent difference between measured and 

known seepage rates ..................................................................... 20

Figure 14. Graph showing boxplots of relative percent difference of bag compliance under 

various test scenarios ..................................................................... 22

Figure 15. Cross-sectional schematic of monitoring well name and location for the 

upstream and downstream transects ................................................... 23

Figure 16. Graphs showing grain-size distribution curves for sediment cores collected at 

the upstream and downstream transects ................................................ 24

Figure 17. Graph showing example of typical recovery time and fit of data for estimating 

hydraulic conductivity by slug test ...................................................... 25

Figure 18. Graphs showing streamflow and temperature histories for gaining and losing 

reaches of a stream coupled to the local ground-water system ..................... 28

Figure 19. Photographs showing bank and in-stream monitoring well pair at downstream 

transect ....................................................................................... 29

Figure 20. Cross-sectional view of instrumented transect .......................................... 30

Figure 21. Photographs showing measurement of spacing for temperature loggers placed in 

in-stream well and placement of temperature loggers in riparian bank well ...... 31

Figure 22. Graphs showing head differences (delta H) between deep and shallow well 

pairs .......................................................................................... 33

Figure 23. Graphs showing temperature profiles collected at instrumented in-stream 

monitoring wells at the downstream transect (transect 1) during the 

study period ................................................................................. 34

Figure 24. Graph showing diurnal scale of temperature profile for monitoring well BW-017 

during June 2004 ........................................................................... 35

Figure 25. Cross-section of downstream transect (transect 1) showing measurement 

locations and model domain ............................................................... 35
vii

Figure 26. Graphs showing plots of observed and simulated temperatures for monitoring 

well RW-044 ................................................................................. 37

Figure 27. Graphs showing plots of observed and simulated temperatures for monitoring 

well RW-035 ................................................................................. 38

Figure 28. Graphs showing results of simulated temperatures with an increase in hydraulic 

conductivity beginning at departure for monitoring well RW-035...................... 39

Tables

Table 1. Description of monitoring equipment in monitoring wells used in this study that 

corresponds with depictions in figure 2 ................................................ 5

Table 2. Objective and description of field measurements using seepage meters............ 14

Table 3. Results of measured and known vertical flux rates, including relative percent 

difference, for collection bag types ...................................................... 19

Table 4. Comparison of test tank flux rate at beginning and end of each test run ............ 21

Table 5. Results of test scenarios using thin-walled packaging collection bags ............ 21

Table 6. Estimated hydraulic conductivity by slug test and (or) grain-size analysis at 

upstream transect (transect 2) ............................................................ 26

Table 7. Estimated hydraulic conductivity by slug test and (or) grain-size analysis at 

downstream transect (transect 1) ......................................................... 26

Table 8. Monitoring well identification number, depth, location, and type of 

data collected .............................................................................. 32

Table 9. Modeling input values of listed parameters for modeling periods listed ............ 39
viii

Abbreviations and Acronyms

(Clarification or additional information given in parentheses)

ACT agricultural chemical transport

BW bank well

i.d. inside diameter

ID identification

K hydraulic conductivity

MW monitoring well

NAWQA National Water-Quality Assessment (USGS)

PVC polyvinyl chloride

RPD relative percent difference

RW river well

VAMP Vernalis Adaptive Management Plan

Organizations

CDWR California Department of Water Resources

MID Modesto Irrigation District

USGS U.S. Geological Survey

Units of measurement

cm centimeter 

cm2 square centimeter

cm/day centimeter per day

cm/s centimeter per second

ft foot (feet)

in. inch

km kilometer

km2 square kilometer

km3 cubic kilometer

m meter

m2 square meter

m3 cubic meter

m/km meter per kilometer

mi mile

m3/s cubic meter per second

mL milliliter (10–3 liter)

mL/min milliliter per minute

mm millimeter (10–3 meter)
ix

Notes:

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

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

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

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

The lower Merced River Basin was chosen by the 

U.S. Geological Survey’s (USGS) National Water Quality 

Assessment Program (NAWQA) to be included in a national 

study on how hydrological processes and agricultural 

practices interact to affect the transport and fate of agricultural 

chemicals. As part of this effort, surface-water–ground-water 

(sw–gw) interactions were studied in an instrumented 100-m 

reach on the lower Merced River. This study focused on 

estimating vertical rates of exchange across the sediment–

water interface by direct measurement using seepage meters 

and by using temperature as a tracer coupled with numerical 

modeling. Temperature loggers and pressure transducers 

were placed in monitoring wells within the streambed and in 

the river to continuously monitor temperature and hydraulic 

head every 15 minutes from March 2004 to October 2005. 

One-dimensional modeling of heat and water flow was 

used to interpret the temperature and head observations 

and deduce the sw–gw fluxes using the USGS numerical 

model, VS2DH, which simulates variably saturated water 

flow and solves the energy transport equation. Results of the 

modeling effort indicate that the Merced River at the study 

reach is generally a slightly gaining stream with small head 

differences (cm) between the surface water and ground water, 

with flow reversals occurring during high streamflow events. 

The average vertical flux across the sediment–water interface 

was 0.4–2.2 cm/day, and the range of hydraulic conductivities 

was 1–10 m/day. Seepage meters generally failed to provide 

accurate data in this high-energy system because of slow 

seepage rates and a moving streambed resulting in scour or 

burial of the seepage meters. Estimates of streambed hydraulic 

conductivity were also made using grain-size analysis and 

slug tests. Estimated hydraulic conductivity for the upstream 

transect determined using slug tests ranged from 40 to 250 

m/day, whereas the downstream transect ranged from 10 to 

100 m/day. The range in variability was a result of position 

along each transect. A relative percent difference was used to 

describe the variability in estimates of hydraulic conductivity 

by grain-size analysis and slug test. Variability in applied 

methods at the upstream transect ranged from 0 to 9 percent, 

whereas the downstream transect showed greater variability, 

with a range of 80 to 133 percent.

Introduction

Hydrologists traditionally regarded streams and ground 

water as distinct, independent resources to be utilized and 

managed separately. However, with increased demands 

on water supplies, hydrologists realized that streams and 

ground water are parts of a single, interconnected resource 

(Winter and others, 1998). Attempts to distinguish these 

resources for analytical or regulatory purposes often meet 

with difficulty because sustained depletions of one resource 

negatively impact the other. An understanding of the 

interconnections between surface water and ground water is 

therefore essential. Scientists have begun to show that local 

hydrologic interactions between surface water and ground 

water play an important role in stream ecosystem structure 

and function (Gilbert and others, 1994; Findlay, 1995; Brunke 

and Gonser, 1997). Water that passes back and forth between 

the surface water and subsurface water influences the fate and 

mobilization of trace metals and organic pollutants, and can 

enhance biogeochemical reactions that can affect downstream 

water quality. Understanding these interactions at small 

scales requires knowledge of ground-water flowpaths and 

their linkages to streams, rates of exchange between stream 

and ground-water systems, and the mechanisms that generate 

spatial (channel unit, reach, and watershed) and temporal 

(diel, seasonal) variations in these processes (Wroblicky and 

others, 1998). Rates of exchange across a streambed are most 

commonly estimated using one or more of the following 

approaches: (1) Darcy water-flux calculations, (2) tracerbased approaches, and (3) direct measurements across a 

streambed using a device such as a seepage meter. The Darcy 

approach calculates water fluxes across streambeds on the 

basis of two-dimensional maps of hydraulic head, estimates 

of hydraulic conductivity of near-channel sediment, and the 

basic governing equations for ground-water flow (Harvey 

and Wagner, 2000). The tracer approach lets one observe 

an introduced tracer (for example, salt, deionized water, or 

bromide) or an environmental tracer (temperature or specific 

conductance) to infer flux rates across the streambed. A 

seepage meter directly measures vertical flux across the 

sediment–water interface.

Estimating Water Fluxes Across the Sediment–Water 

Interface in the Lower Merced River, California

By Celia Zamora 
2 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Background

The Merced River, located in the San Joaquin River 

Basin in central California, was chosen by the U.S. Geological 

Survey’s (USGS) National Water-Quality Assessment 

(NAWQA) Program as one of five study areas in a national 

study of how hydrological processes and agricultural practices 

interact to affect the transport and fate of agricultural 

chemicals in nationally important agricultural settings. The 

key to achieving this objective is an understanding of how 

the agricultural chemicals move through each hydrologic 

compartment, as well as estimating rates of exchange between 

compartments. Five hydrologic compartments were monitored: 

the atmosphere, surface water, the unsaturated zone, ground 

water, and the hyporheic zone (surface-water–ground-water, 

or sw–gw, interaction). This project focused on estimating 

rates of exchange between the surface water and ground water 

across the sediment–water interface in the lower Merced 

River, California.

Estimates of ground-water seepage were made along 

a 100-m reach in the lower Merced River. The site location 

was chosen on the basis of reconnaissance work. The 

criteria required that the reach be gaining, easily accessible, 

and located next to agricultural land on which agricultural 

chemicals of interest were being applied. The location of the 

reach also bracketed the end of the ground-water flowpath 

compartment and was near the atmosphere and unsaturated 

zone compartment in the adjacent almond orchard. 

Purpose and Scope

This report provides information regarding the use of 

seepage meters in a river environment and the application of 

temperature as a tracer in the shallow riverbed subsurface to 

predict rates of exchange using a USGS heat and flow model. 

Vertical estimates of ground-water seepage rates through a 

100-m reach of the Merced River, California, are presented. 

Seepage rates were estimated directly using seepage meters, 

and indirectly using temperature and head measurements to 

calibrate a flow and heat transport model, VS2DH. Indirect 

seepage rates were constrained by hydraulic conductivity 

estimates from sieve analysis of streambed sediments and slug 

tests.

Study Area

The study area is located in the lower Merced River 

Basin, which lies on the east side of the San Joaquin Valley 

in the San Joaquin Basin and is approximately 831 km2

(fig.1). Two transects across a 100-m reach were equipped 

with monitoring wells that recorded continuous temperature 

and pressure head throughout the study period (fig. 2 and 

table 1). Table 1 describes the location and type of monitoring 

equipment depicted in figure 2. The lower Merced River Basin 

setting is predominately agriculture on the valley floor and 

lies within the flat structural basin of the San Joaquin Valley. 

The upstream part of the lower basin extends eastward into the 

lower foothills of the Sierra Nevada. The San Joaquin Valley 

is bounded by the Sierra Nevada to the east, the Coast Ranges 

to the west, the Tehachapi Mountains to the south, and the 

Sacramento–San Joaquin Delta to the north. The boundary of 

the basin is defined by the topographic drainage divides and 

in some areas, by canals and laterals that serve this area. The 

altitude ranges from 22 m in the San Joaquin Valley to 168 

m above sea level in the Sierra Nevada foothills. Elevation 

gradients average about 2.5 m/km on the valley floor and 

26.7 m/km in the foothills (Gronberg and Kratzer, 2006). 

Approximately 55 percent of the lower Merced River Basin 

is covered by agricultural land; 39 percent is forest, shrub 

land, and grassland; over 4 percent is urban and transitional 

land; and less than 2 percent is water and wetland (Vogelmann 

and others, 2001). The forest, shrub land, and grassland are 

predominantly on the valley floor.

Geology

The San Joaquin Valley is part of the Central Valley, 

which is a large, northwest-trending, asymmetric structural 

trough, filled with marine and continental sediments (Bartow, 

1991). To the east of the valley, the Sierra Nevada is composed 

primarily of pre-Tertiary granitic rocks and is separated 

from the valley by a foothill belt of marine and metavolcanic 

rocks. The Coast Ranges west of the valley are a complex 

assemblage of rocks, including marine and continental 

sediments of the Cretaceous to Quaternary Periods (Page, 

1977; Page 1986). Alluvial deposits of the eastern part of 

the valley were derived primarily from the weathering of 

granitic instrusive rocks of the Sierra Nevada, and are highly 

permeable, medium- to coarse-grained sands with low total 

organic carbon, forming broad alluvial fans where the streams 

enter the valley. These deposits generally are coarsest near 

the upper parts of the alluvial fans and finest near the valley 

trough. Dune sand, derived from the alluvial deposits, consists 

of well-sorted medium-to-fine sand, as much as 43-m thick 

(Page, 1986). Stream-channel deposits along the Merced River 

consist of medium-to-coarse sand with silty-clay layers (~2 

cm–60 cm) in the shallow subsurface.

Consolidated rocks and deposits exposed along the 

margin of the valley floor include Tertiary and Quaternary 

continental deposits, Cretaceous and Tertiary marine 

sedimentary rocks, and the pre-Tertiary Sierra Nevada 

basement complex (Davis and Hall, 1959; Croft, 1972; Page 

and Balding, 1973). Most of the unconsolidated deposits in 

the study area are contained within the Pliocene–Pleistocene 

Laguna, Turlock Lake, Riverbank, and Modesto Formations, 

with minor amounts of Holocene stream-channel and floodbasin deposits. The Turlock Lake, Riverbank, and Modesto 

Formations form a sequence of overlapping channel incisions 

that were influenced by climatic fluctuations, and resultant 

glacial stages in the Sierra Nevada (Bartow, 1991).
Introduction 3

Figure 1. Study area and locations of fixed transect 1 and transect 2 in the lower Merced Basin. Arrow indicates direction of 

streamflow. 

37°

37'

30"

Highline Canal

Urban

Orchard

Vineyard

Other agriculture

Pasture

Native vegetation

EXPLANATION

120 48 40 120 48 30 120 48 20

37 22 30

37 30

120 45

120 30

120 48 10 120 48

Transect 1

Transect 2

San

Joaquin

Basin

Tulare

Basin

San

Joaquin

Valley

Study

Area

San

Francisco

California

37

23

30

37

23

20

37

23

10

Mustang Creek

Dry Creek

Highline Canal

Merced River

37 39’ N

120 59’ W

0 300 600 FEET

0 50 100 METERS

0 5 10 MILES

0 5 10 KILOMETERS

Study area:

Lower Merced Basin

Modesto
4 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

The Corcoran Clay, at the base of the upper Turlock Lake 

Formation, is a lacustrine deposit that is a key subsurface 

feature in the San Joaquin Valley. Page (1986) mapped 

the areal extent of this regional aquitard on the basis of a 

limited number of well logs and geophysical logs. Additional 

lithologic data recently were used to modify the mapped 

extent of this important unit (Burow and others, 2004). The 

eastern extent of the Corcoran Clay roughly parallels the San 

Joaquin River valley axis. The Corcoran Clay ranges in depth 

from 28 to 85 m below land surface and a thickness from 0 to 

57 m in the study area.

001

002

003

004

005

006

011

012

009 010

007

008

051

052

053

054

055

043

043

044

044

045

046

047

034

034 035

035

036

037

038

016

026

027

028

029

025

107

108

109

110

098

098

106

071

080

072

073

074

075

081

082

083

084

090

090

091

092

093

099

099

100

101

102

089

089

EXPLANATION

Monitoring well

Seepage meter

Temperature logger

Pressure transducer

017

017

018

019

020

Transect 1

(downstream)

Transect 2

(upstream)

701

701

701

0 0.05 0.1 MILES

0 0.05 0.1 KILOMETERS

Merced River

120 48 15 120 48 10 120 48 05

37

23

15

37

23

10

Figure 2. Location of monitoring wells and monitoring equipment at fixed transects 1 and 2 in the lower Merced Basin.

Arrow in upper right on map indicates direction of streamflow.
Introduction 5

Table 1. Description of monitoring equipment in monitoring wells used in this study that corresponds with depictions in figure 

2—Continued.

[BLW, below; ID, identification; LSD, land surface datum; M, m, meter; MI, mile; NR, near; PVC, polyvinyl chloride; R, river; TEMP, temperature; US, 

upstream; USGS, U.S. Geological Survey. Map symbols: ♦, seepage meter; ●, monitoring well; ▼, pressure transducer; ■, temperature logger]

Map ID 

number

Map 

symbol Monitoring equipment USGS site ID USGS site name

001 ♦ seepage meter 372312120481001 SEEPAGE METER “D” 11.2 MI US MERCED R 

NR STEVINSON

002 ♦ seepage meter 372312120481002 SEEPAGE METER “4” 11.2 MI US MERCED R 

NR STEVINSON

003 ♦ seepage meter 372312120481003 SEEPAGE METER “E” 11.2 MI US MERCED R 

NR STEVINSON

004 ♦ seepage meter 372312120481004 SEEPAGE METER “5” 11.2 MI US MERCED R 

NR STEVINSON

005 ♦ seepage meter 372312120481005 SEEPAGE METER “F” 11.2 MI US MERCED R 

NR STEVINSON

006 ♦ seepage meter 372312120481006 SEEPAGE METER “6” 11.2 MI US MERCED R 

NR STEVINSON

007 ♦ seepage meter 372312120481007 SEEPAGE METER “A” 11.3 MI US MERCED R 

NR STEVINSON

008 ♦ seepage meter 372312120481008 SEEPAGE METER “1” 11.3 MI US MERCED R 

NR STEVINSON

009 ♦ seepage meter 372312120481009 SEEPAGE METER “B” 11.3MI US MERCED R 

NR STEVINSON

010 ♦ seepage meter 372312120481010 SEEAPGE METER “2” 11.3 MI US MERCED R 

NR STEVINSON

011 ♦ seepage meter 372312120481011 SEEPAGE METER “C” 11.3 MI US MERCED R 

NR STEVINSON

012 ♦ seepage meter 372312120481012 SEEPAGE METER “3” 11.3 MI US MERCED R 

NR STEVINSON

016 ● monitoring well screened 3.5 m below 

land surface

372312120481016 006S011E30B019M

017 ● monitoring well screened 5 m below land 

surface

372312120481017 006S011E30B018M

017 ▼ pressure transducer 372312120481017 006S011E30B018M 

018 ■ temperature logger 3.5 m below land 

surface

372312120481018 006S011E30B018M WATER TEMP-LOGGER AT 

350CM BLW PVC

019 ■ temperature logger 4 m below land 

surface

372312120481019 006S011E30B018M WATER TEMP-LOGGER AT 

400CM BLW PVC

020 ■ temperature logger 5 m below land 

surface

372312120481020 006S011E30B018M WATER TEMP-LOGGER AT 

500CM BLW PVC

025 ● monitoring well screened 0.5 m below 

streambed

372312120481025 006S011E30B017M

026 ● monitoring well screened 3 m below 

streambed

372312120481026 006S011E30B016M

027 ■ temperature logger 0.5 m below 

streambed

372312120481027 006S011E30B016M WATER TEMP LOGGER AT 

0.5M BLW LSD

028 ■ temperature logger 1 m below streambed 372312120481028 006S011E30B016M WATER TEMP LOGGER AT 

1.0M BLW LSD

029 ■ temperature logger 2 m below streambed 372312120481029 006S011E30B016M WATER TEMP LOGGER AT 

2.0M BLW LSD

034 ● monitoring well screened 0.5 m below 

streambed

372312120481034 006S011E30B015M

034 ▼ pressure transducer 372312120481034 006S011E30B015M

035 ● monitoring well screened 3 m below 

streambed

372312120481035 006S011E30B014M

035 ▼ pressure transducer 372312120481035 006S011E30B014M

036 ■ temperature logger 0.5 m below 

streambed

372312120481036 006S011E30B014M WATER TEMP LOGGER AT 

0.5M BLW LSD

Table 1. Description of monitoring equipment in monitoring wells used in this study that corresponds with depictions in figure 2.

[BLW, below; ID, identification; LSD, land surface datum; M, m, meter; MI, mile; NR, near; PVC, polyvinyl chloride; R, river; TEMP, temperature; US, 

upstream; USGS, U.S. Geological Survey. Map symbols: ♦, seepage meter; ●, monitoring well; ▼, pressure transducer; ■ , temperature logger]
6 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Table 1. Description of monitoring equipment in monitoring wells used in this study that corresponds with depictions in figure 

2—Continued.

[BLW, below; ID, identification; LSD, land surface datum; M, m, meter; MI, mile; NR, near; PVC, polyvinyl chloride; R, river; TEMP, temperature; US, 

upstream; USGS, U.S. Geological Survey. Map symbols: , seepage meter; , monitoring well; ▼, pressure transducer; , temperature logger]

Map ID 

number

Map 

symbol Monitoring equipment USGS site ID USGS site name

037 ■ temperature logger 1.0 m below 

streambed

372312120481037 006S011E30B014M WATER TEMP LOGGER AT 

1.0M BLW LSD

038 ■ temperature logger 2.0 m below 

streambed

372312120481038 006S011E30B014M WATER TEMP LOGGER AT 

2.0M BLW LSD

043 ● monitoring well screened 0.5 m below 

streambed

372312120481043 006S011E30B013M

043 ▼ pressure transducer 372312120481043 006S011E30B013M

044 ● monitoring well screened 3 m below 

streambed

372312120481044 006S011E30B012M

044 ▼ pressure transducer 372312120481044 006S011E30B012M

045 ■ temperature logger 0.5 m below 

streambed

372312120481045 006S011E30B012M WATER TEMP LOGGER AT 

0.5M BLW LSD

046 ■ temperature logger 1.0 m below 

streambed

372312120481046 006S011E30B012M WATER TEMP LOGGER AT 

1.0M BLW LSD

047 ■ temperature logger 2.0 m below 

streambed

372312120481047 006S011E30B012M WATER TEMP LOGGER AT 

2.0M BLW LSD

051 ● monitoring well screened 3.5 m below 

land surface

372312120481051 006S011E30B011M

052 ● monitoring well screened 5 m below land 

surface

372312120481052 006S011E30B010M

053 ■ temperature logger 3.5 m below land 

surface

372312120481053 006S011E30B010M WATER TEMP-LOGGER AT 

350CM BLW PVC

054 ■ temperature logger 4 m below land 

surface

372312120481054 006S011E30B010M WATER TEMP-LOGGER AT 

400CM BLW PVC

055 ■ temperature logger 5 m below land 

surface

372312120481055 006S011E30B010M WATER TEMP-LOGGER AT 

500CM BLW PVC

071 ● monitoring well screened 3.5 m below 

land surface

372312120481071 006S011E30B029M

072 ● monitoring well screened 5 m below land 

surface

372312120481072 006S011E30B028M

073 ■ temperature logger 3.5 m below land 

surface

372312120481073 006S011E30B028M WATER TEMP-LOGGER AT 

350CM BLW PVC

074 ■ temperature logger 4 m below land 

surface

372312120481074 006S011E30B028M WATER TEMP-LOGGER AT 

400CM BLW PVC

075 ■ temperature logger 5 m below land

surface

372312120481075 006S011E30B028M WATER TEMP-LOGGER AT 

500CM BLW PVC

080 ● monitoring well screened 0.5 m below 

streambed

372312120481080 006S011E30B027M

081 ● monitoring well screened 3 m below 

streambed

372312120481081 006S011E30B026M

082 ■ temperature logger 0.5 m below 

streambed

372312120481082 006S011E30B026M WATER TEMP LOGGER AT 

0.5M BLW LSD

083 ■ temperature logger 1 m below streambed 372312120481083 006S011E30B026M WATER TEMP LOGGER AT 

1.0M BLW LSD

084 ■ temperature logger 2 m below streambed 372312120481084 006S011E30B026M WATER TEMP LOGGER AT 

2.0M BLW LSD

089 ● monitoring well screened 0.5 m below 

streambed

372312120481089 006S011E30B025M

089 ▼ pressure transducer 372312120481089 006S011E30B025M

090 ● monitoring well screened 3 m below 

streambed

372312120481090 006S011E30B024M

090 ▼ pressure transducer 372312120481090 006S011E30B024M
Introduction 7

Climate

The San Joaquin Valley has an arid-to-semiarid climate 

that is characterized by hot summers and mild winters. 

Average temperatures are fairly uniform over the valley 

floor. Temperature decreases with increasing elevation in 

the foothills and mountains of the Sierra Nevada. Long-term 

records for temperature do not exist for sites within the lower 

Merced River Basin. However, the Modesto Irrigation District 

(MID) has temperature data for downtown Modesto from 

1939 to 2005 (Modesto Irrigation District, 2005). Mean low 

temperatures in degrees Fahrenheit range from mid-30s in 

the winter months to upper 50s in the summer. Mean high 

temperatures in degrees Fahrenheit range from mid-50s in 

the winter months to mid-90s in the summer (Gronberg and 

Kratzer, 2006). As with temperature, long-term precipitation 

records do not exist within the lower Merced River Basin. 

However, MID does have long-term precipitation record 

for Modesto from 1889 to 2005. Mean annual precipitation 

(1889–2005) in Modesto is 31 cm, but annual precipitation is 

highly variable. Eighty percent of the precipitation falls during 

November through March, with the maximum precipitation in 

December through February.

Table 1. Description of monitoring equipment in monitoring wells used in this study that corresponds with depictions in figure 

2—Continued.

[BLW, below; ID, identification; LSD, land surface datum; M, m, meter; MI, mile; NR, near; PVC, polyvinyl chloride; R, river; TEMP, temperature; US, 

upstream; USGS, U.S. Geological Survey. Map symbols: , seepage meter; , monitoring well; ▼, pressure transducer; , temperature logger]

Map ID 

number

Map 

symbol Monitoring equipment USGS site ID USGS site name

091 ■ temperature logger 0.5 m below 

streambed

372312120481091 006S011E30B024M WATER TEMP LOGGER AT 

0.5M BLW LSD

092 ■ temperature logger 1 m below streambed 372312120481092 006S011E30B024M WATER TEMP LOGGER AT 

1.0M BLW LSD

093 ■ temperature logger 2 m below streambed 372312120481093 006S011E30B024M WATER TEMP LOGGER AT 

2.0M BLW LSD

098 ● monitoring well screened 0.5 m below 

streambed

372312120481098 006S011E30B023M

098 ▼ pressure transducer 372312120481098 006S011E30B023M

099 ● monitoring well screened 3 m below 

streambed

372312120481099 006S011E30B022M

099 ▼ pressure transducer 372312120481099 006S011E30B022M

100 ■ temperature logger 0.5 m below 

streambed

372312120481100 006S011E30B022M WATER TEMP LOGGER AT 

0.5M BLW LSD

101 ■ temperature logger 1 m below streambed 372312120481101 006S011E30B022M WATER TEMP LOGGER AT 

1.0M BLW LSD

102 ■ temperature logger 2 m below streambed 372312120481102 006S011E30B022M WATER TEMP LOGGER AT 

2.0M BLW LSD

106 ● monitoring well screened 3.5 m below 

land surface

372312120481106 006S011E30B021M

107 ● monitoring well screened 5 m below land 

surface

372312120481107 006S011E30B020M

108 ■ temperature logger 3.5 m below land 

surface

372312120481108 006S011E30B020M WATER TEMP-LOGGER AT 

350CM BLW PVC

109 ■ temperature logger 4 m below land 

surface

372312120481109 006S011E30B020M WATER TEMP-LOGGER AT 

400CM BLW PVC

110 ■ temperature logger 5 m below land 

surface

372312120481110 006S011E30B020M WATER TEMP-LOGGER AT 

500CM BLW PVC

701 ● monitoring well screened above 

sediment/water interface

372316120480701 MERCED R NR RIVER MILE 16 NR DELHI CA

701 ▼ pressure transducer 372316120480701 MERCED R NR RIVER MILE 16 NR DELHI CA

701 ■ temperature logger 372316120480701 MERCED R NR RIVER MILE 16 NR DELHI CA
8 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Surface-Water Hydrology

The surface-water hydrology of the Merced River Basin 

has been significantly modified by the development of water 

resources. Between the 1870s and early 1900s, many canals 

were constructed to transport water to the land. Exchequer 

Dam was completed in 1926 to provide flood control and 

water for irrigation and power generation. In 1967, New 

Exchequer Dam was completed to expand Lake McClure 

Reservoir’s capacity to 1.26 km3. In the same year, McSwain 

Dam was completed downstream as a regulating reservoir. 

Downstream of McSwain Dam, the Merced Falls Dam diverts 

flow into the MID’s Northside Canal to provide irrigation 

water to areas north of the Merced River. Farther downstream, 

Crocker-Huffman Dam diverts flow into the MID’s Main 

Canal (Stillwater Sciences and EDAW, 2001). The area of 

focus for this study, the lower Merced River Basin, starts at 

New Exchequer Dam. Water quality above this point generally 

is unaffected by agricultural activities. The lower Merced 

River receives water from Dry Creek and from Mustang Creek 

by way of the Highline Canal. 

Mean annual streamflow measured at the California 

Department of Water Resources (CDWR) Merced River near 

Stevinson gaging station (24 km downstream of the study site) 

is approximately 19.6 m3/s for water years 1941–2005. Mean 

annual streamflow for this period varies greatly from year to 

year. The recent water years 2003–2004 had below-normal 

streamflow, whereas 2005 had above-average streamflow 

attributed to above-average snow pack in the Sierra Nevada 

above New Exchequer Dam (fig. 3). In a natural basin, the 

usual trend is to see a higher streamflow downstream as the 

area of contribution increases. However, because the Merced 

River is highly engineered and utilized for agricultural 

irrigation, it has an overall decrease in streamflow from the 

upper basin to the mouth.

Ground-Water Hydrology

Ground water in the lower Merced Basin occurs primarily 

in the unconfined aquifer above and east of the Corcoran Clay 

and in the confined aquifer beneath the Corcoran Clay. The 

unconfined aquifer above the clay ranges in thickness from 

about 40 to 70 m. The unconfined aquifers east of the clay are 

composed primarily of alluvial sediment, but include the upper 

part of the Mehrten Formation, which is more consolidated 

than the overlying formations. The confined aquifer is 

composed of alluvial sediments and upper Mehrten Formation 

sediments from beneath the clay to the base of fresh water 

(Steven Phillips, USGS, written commun., 2006).

0

25

50

75

100

1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

WATER YEAR

MEAN ANNUAL STREA

MFLOW, IN CUBIC METERS PER SECOND

USGS, Mean annual streamflow, m3/s

CDWR, Mean annual streamflow, m3

/s

Mean, 19.6 m3/s

Merced River near Stevinson (11272500)

Figure 3. Mean annual streamflow, Merced River near Stevinson, California, water years 1941–2005 (from California Department 

of Water Resources, 2006). Number in parentheses is the USGS site identification number (CDWR, California Department of Water 

Resources; m3/s, cubic meters per second; USGS, U.S. Geological Survey).
Seepage Measurements 9

Under natural conditions, ground-water recharge 

occurs primarily at the upper parts of the alluvial fans from 

streams entering the valley. Prior to ground-water resource 

development, most ground water had been discharged as 

evapotranspiration in the central trough of the valley, and to a 

lesser extent, to streams. Water-resource development in the 

basin has changed the ground-water flow regime. Pumping 

for agricultural irrigation and irrigation return flows are much 

greater than natural recharge and discharge and cause an 

increase in vertical flow in the system. Ground-water flow 

is generally toward the southwest and is somewhat similar 

to the predevelopment flow regime (Gronberg and Kratzer, 

2006). However, ground water moving along a horizontal 

flowpath commonly is extracted by wells and reapplied at the 

surface several times before reaching the valley trough (Steven 

Phillips, USGS, written commun., 2006).

Seepage Measurements

The seepage meter allows direct measurement of seepage 

flux across the sediment–water interface. It consists of a 

bottomless cylinder formed from an inverted drum or bucket 

connected to a collection bag by a length of tubing. The device 

is pushed into the bed of a lake or stream, and a collection bag 

with a known volume of water is attached. The collection bag 

is then removed after a period of elapsed time, and the rate of 

vertical ground-water flux through the area enclosed by the 

seepage meter is calculated from the increase or decrease in 

the initial volume of water, the length of time elapsed, and 

the area of the seepage meter, yielding flux rates in units of 

length/time. An increase in the initial volume indicates a 

positive vertical flux rate (ground water to surface water), and 

a decrease in initial volume indicates a negative vertical flux 

rate (surface water to ground water). 

Review of Literature

The seepage meter was initially developed to measure 

losses from irrigation canals (Israelsen and Reeve, 1944), and 

in the mid-1970s, the design was improved and the use was 

expanded to measure ground-water discharge into lakes (Lee, 

1977; Lee and Cherry, 1978; John and Lock, 1977; Connor 

and Belanger, 1981; Erickson, 1981; Woessner and Sullivan, 

1984; Isiorho and Matisoff, 1990; Shaw and Prepas, 1990b; 

Lesack, 1995; Rosenberry, 2000; Sebestyen and Schneider, 

2001). Because seepage meters provide a quick and simple 

method for gathering information on the direction, rate, and 

variability of seepage flux across the sediment–water interface, 

their use has been expanded to environments other than lakes. 

Vertical seepage rates have been measured in wetlands (Choi 

and Harvey, 2000), estuaries (Lee, 1977; Lock and John, 1978; 

Zimmerman and others, 1985; Yelverton and Hackney, 1986; 

Boyle, 1994; Linderfelt and Turner, 2001) and nearshore ocean 

margins (Cable and others, 1997; Shinn and others, 2002; 

Taniguchi, 2002; Chanton and others, 2003). Seepage meters 

have also been used to determine water budgets (Fellows and 

Brezonik, 1980) or to obtain samples for chemical analysis 

(Lee, 1977; Downing and Perterka, 1978; Brock and others, 

1982; Belanger and Mikutel, 1985; Shaw and others, 1990). 

A growing interest in investigating the rates of exchange 

between streams and ground water has led to the use of 

seepage meters in stream channels (Lee and Hynes, 1977; 

Connor and Belanger, 1981; McBride, 1987; Libelo and 

MacIntyre, 1994; Blanchefield and Ridgeway, 1996; Jackman 

and others, 1997; Cey and others, 1998; Fryar and others 

2000; Dumouchelle, 2001; Landon and others, 2001; Murdoch 

and Kelly, 2003). However, the data obtained are often highly 

variable because the original design and application were 

intended for lake and estuary environments, where issues of 

current and scour are generally negligible. As discussed in 

more detail later in this section, significant streamflow rates 

may create hydraulic pressure on the measure bag, creating 

erroneous gains or losses in the bag volume over time. Scour 

may lead to a breach in the hydraulic seal around the seepage 

meter. Flume and laboratory studies show that much of this 

variation is due to the effects of flow across the seepage meter 

collection bag, which alters the hydraulic head within the 

meter and induces seepage flow (Libelo and MacIntyre, 1994). 

Their study discovered that the induced seepage flow can be 

significantly reduced by isolating the seepage meter collection 

bag from the streamflow. 

Concerns over the effects that size, thickness, and initial 

conditions of the attached collection bag have on measured 

seepage rates have prompted investigations in field and 

laboratory settings. Shaw and Prepas (1989) found that an 

anomalous, short-term influx of water into seepage meters 

occurred immediately after connecting the collection bag 

to the seepage meter, but showed that the anomaly could be 

effectively eliminated by attaching prefilled collection bags 

with a minimum of 1,000 mL before attaching to the seepage 

meter. The effects of bag type and meter size on seepagemeter measurements were evaluated in a laboratory setting 

by Isiorho and Meyer (1999). Their study found that there 

was no significant difference attributed to bag type, but found 

that smaller diameter seepage meters had a greater variance. 

Laboratory studies have also examined bag conductance, 

which is the ratio of the volumetric flow rate into the bag to 

the hydraulic head required to fill the bag (Murdoch and Kelly, 

2003). Harvey and Lee (2000) found that the conductance of a 

bag formed from a thin compliant film is expected to be large 

and relatively constant until it is filled with enough water to 

cause stretching, at which point conductance will decrease. 

The conductance of a bag may also vary if the bag deforms 

in an irregular manner and will decrease if kinks or folds 

develop in the bag (Kelly, 2001). As a collection bag opens 

and approaches its manufactured shape, a gradual decrease in 

conductance of the bag with increasing volume was observed 

by Schincariol and McNeil (2002). Similar results were 

observed by Shaw and Prepas (1989) and Blanchfield and 

Ridgeway (1996). 
10 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

In field settings, slow seepage rates and the relatively 

small area measured also present problems. Very slow seepage 

rates may require a meter to be in place for several days. The 

problem of measurement area is of concern because most 

researchers and watershed managers are interested in seepage 

processes on a scale of hundreds to thousands of square 

meters or more, and most seepage meters typically integrate 

vertical flux over an area of approximately 0.25 m2 or less 

(Rosenberry, 2005). Rosenberry addressed these issues in a 

low-permeability zone by connecting multiple seepage meter 

cylinders together to a single collection bag to increase the 

area represented by each measurement, thus integrating spatial 

heterogeneity over a larger area and reducing the time required 

to collect a measurable change in volume.

Some investigators (Erickson, 1981; Brock and others, 

1982; Woessner and Sullivan, 1984; Shaw and Prepas, 1990a; 

Blanchfield and Ridgeway, 1996; Harvey and Lee, 2000) 

using seepage meters have expressed guarded concerns that 

the performance of the meter itself may cause variability 

that is unrelated to, and can obscure, the natural processes 

that they are trying to characterize (Schincariol and McNeil, 

2002). Erickson (1981) stated that seepage meters disturb the 

flow field in which they are installed, resulting in consistently 

lower measured seepage rates. This disturbance is apparently 

related to frictional resistance along the internal boundaries of 

the meter. Frictional resistance is inherent to some extent in 

all seepage meter designs, and as a result, several laboratory 

studies have come up with a seepage meter coefficient that 

is used to convert measured seepage rates to true values. 

Coefficients in the literature range from 1.1 to 1.7 (Erickson, 

1981; Cherkauer and McBride, 1988; Asbury, 1990; Belanger 

and Montgomery, 1992). Many of the less efficient meter 

designs require larger coefficients primarily because they 

use small-diameter tubing to connect the bag to the seepage 

cylinder (Rosenberry, 2005). The use of large-diameter 

plumbing greatly reduces loss of efficiency, resulting in a 

smaller correction coefficient (Fellows and Brezonik, 1980; 

Rosenberry, 2005). 

Murdoch and Kelly (2003) developed a theoretical 

analysis to evaluate the extent to which bag conductance and 

velocity head may affect flux measurements by a seepage 

meter. Their analysis showed that bag conductance, radius 

of the seepage meter, and hydraulic conductivity of the 

streambed can be combined to give a dimensionless term 

that characterizes seepage meter performance. Some seepage 

meters use electronic flowmeters (Paulsen and others, 2001; 

Taniguchi and Fukuo, 1993; Rosenberry and Morin, 2004) 

to eliminate problems encountered with the collection bag. 

Although these devices show promise, their availability and 

expense make their use limited. This study focused on the 

conventional seepage meter that is both inexpensive and easily 

fabricated.

The purpose of using seepage meters to directly 

measure seepage rates was to gain an overall understanding 

of the direction, rate, and variability of seepage rates within 

the study area. The seepage meters used in this study 

incorporated suggestions made by several investigators 

(Libelo and MacIntyre, 1994; Shaw and Prepas, 1989; 

Kelly, 2001; Murdoch and Kelly, 2003) in an attempt to 

minimize variability in measured vertical seepage rates. The 

performance of the collection bags used in this study was 

measured in a laboratory test tank, and improvements were 

made to seepage meters and collection bags as a result of 

laboratory test results.

Field Measurements

Field Methods

Flux rates across the sediment–water interface were 

measured directly using twelve drum-style (Lee, 1977) 

seepage meters. Two sizes of seepage meters were used: 

the larger meters were 2,500 cm2 in cross-sectional area 

and 26.5-cm deep, and the smaller meters were 620 cm2 in 

cross-sectional area and 13.5-cm deep. The field deployment 

methods for both sizes of meters was to carefully push each 

meter into the riverbed sediment, leaving approximately 5 

cm of the top of each meter above the streambed bottom. 

The deployment array of the seepage meters placed in the 

streambed involved pairing a large and small seepage meter 

spaced approximately 1.5 m apart. The purpose of pairing 

the meters was to compare flux rates between seepage meter 

pairs and observe variability in measured rates for the same 

size meter at different parts of the array over consecutive 

measurements. Two deployment arrays were used throughout 

the study. The first deployment array involved placing the 

six paired meters perpendicular to flow across two transects 

that were separated by a distance of approximately 10 m, and 

the second deployment array placed the paired meters across 

two transects separated by a distance of approximately 100 m 

(fig. 4). The seepage-meter pairs will be referred to as A-1, 

B-2, C-3, and so on. 

The meters were then left undisturbed for 12 to 24 hours 

to allow trapped air to escape, as well as to permit riverbed 

sediments to return to equilibrium after being disturbed 

during installation. Once deployed, the meters were left in 

place for the duration of the measuring event. Following the 

equilibration period, the collection bags were prefilled with 

500–1,000 mL of water, placed in housing units to protect the 

bag from the flow of the river, and connected to the seepage 

meters. The collection bags and housing units were connected 

to the seepage meters using a 61-cm length of 0.64-cm-i.d. 

(inside diameter) vinyl tubing. The housing unit for the large, 

seepage-meter bag was a perforated plastic storage box that 

was secured to the top of the seepage meter with a bungee 

cord. The small seepage meter used the half of a drum as the 

housing unit for the collection bag and was simply pushed into 

the sediment alongside the seepage meter (figs. 5 and 6). 
Seepage Measurements 11

Careful attention was given to avoid disturbing the 

sediments around each of the paired meters, and the 

attachment and retrieval of collection bags was performed by 

snorkeling to and from each meter to eliminate any contact 

with the riverbed bottom. Because of the slow flux rates 

encountered, the collection bags were retrieved and redeployed 

approximately every 12–24 hours over a few days. The change 

in volume was either measured using a graduated cylinder or 

weighed with a scale, and the elapsed time was recorded. The 

change in volume (mL/min) over the elapsed time (days) was 

divided by the cross-sectional area of the seepage meter (cm2) 

to obtain vertical flux rates in cm/day. 

A

B

right bank left bank

Streamflow direction

Streamflow direction

right bank left bank

A C E

B D F

2 4 6

1 3 5

A

1

B

2

C

3

D

4

E

5

F

6

Figure 4. Seepage meter arrays at transects 1 and 2. A. Array 1. B. Array 2.
12 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

A B

Figure 5. Seepage meters. A. Large seepage meter with attached housing unit. B. Small seepage meter with housing unit.

Streamflow direction

Figure 6. Field deployment of paired seepage meters.
Seepage Measurements 13

Three types of collection bags were used in the study. 

The collection bag types used were an 1,800-mL Sun Shower 

Solar Bag, a 2,000-mL medical urine collection bag, and a 

2,000-mL Void-Fill packaging bag. These collection bags 

will be referred to as shower bag, medical bag, and packaging 

bag, respectively. Initial field measurements used only the 

shower and medical collection bags attached to the large and 

small seepage meters, respectively. However, the results of 

laboratory test runs prompted exclusive use of the packaging 

collection bag in seepage rate measurements made in the latter 

part of the study. 

A total of six sampling events were made over a period 

of 10 months beginning in December 2003 and ending 

in September 2004. The planned period for each field 

measurement was initially intended to be one week. However, 

stream scour around the seepage meters resulted in only two 

or three repeat measurements taken over 48–72 hours. Because 

improvements were made to the seepage meter and collection 

bags over the period of the study, the objective and methods 

of each field visit are discussed individually and are listed in 

table 2.

Field Results

Seepage meters did not work because of bed load 

movement in the upper 0.5 m of the Merced River. 

Observations of the streambed during site visits revealed 

that the stream bottom is continually moving—small dunes 

would develop and disappear several hours later. The problem 

was further compounded by the slow seepage rates, which 

required the seepage meters to be in place for several days 

and be subjected to the moving streambed, resulting in scour 

at the base of the meter(s) (fig. 7). Scoured-out seepage 

meters took in river water and filled the collection bag to 

maximum capacity, resulting in erroneously high seepage 

rates. In addition, the housing unit for the small seepage 

meter was not as effective as the housing unit for the large 

seepage meter. The housing units would scour out, become 

dislodged, and expose the collection bag to the flow of the 

river, thereby inducing volumetric flow into the collection bag. 

In other cases, the housing unit would become buried under 

the streambed sediments resulting in complete loss of initial 

volume.

The original intent of pairing the seepage meters was 

to compare flux rates between the two sizes. In most cases, 

the flux direction was opposing, and for pairs in which the 

flux direction was the same for both sizes, the difference in 

rates often was too great to provide meaningful results. In 

addition, variability existed in the measured flux rates between 

the same size meters over consecutive measurement periods. 

Low flux rates (<3 cm/day) and a moving streambed resulted 

in scour or burial of seepage meters. As a result, only two 

consecutive 24-hour measurement periods could be made for 

each seepage meter. Figures 8, 9, and 10 depict the variability 

in measurements described above for each meter over the six 

sampling events. The Appendix lists the results of each of the 

six sampling events. 

The smaller seepage meters (numbered seepage meters in 

figs. 8, 9, and 10) showed greater variability over consecutive 

measurements than the larger seepage meters, consistent 

with the findings of Isiorho and Meyer (1999). The results 

of the January and February 2004 (sampling events 3 and 

4) gave inconclusive results for comparisons made between 

measured rates using shower and medical collection bags 

and comparison of those rates with measured rates using the 

packaging bags (Appendix). However, repeat measurements 

made with the shower bag attached to the large seepage meter 

gave consistent results. During the January 2004 visit, seepage 

meter B measured rates of 0.21 and 0.24 cm/day in two repeat 

measurements, and seepage meter C measured the same 

seepage rate, 0.15 cm/day, over a 48-hour period. The same 

pattern resulted for seepage meter A during the February 2004 

visit, which measured a flux rate of 0.20 and 0.17 cm/day for 

consecutive measurements. The July and September 2004 

site visits (sampling events 5 and 6) used only the thin-walled 

packaging bags attached to both meters, and inconsistencies 

in direction and magnitude of measured rates indicated no 

apparent pattern in seepage rates. 

It was unclear whether the variability observed between 

the two types of seepage meters was a result of spatial 

variability in the hyporheic flowpaths at the sediment–water 

interface, a result of scour and burial problems encountered 

with the seepage meters, or unexplainable factors affecting 

the performance of the seepage meters and (or) collection 

bags. Because only two or three repeat measurements could 

be made at each of the field visits before the meters were 

scoured out, the seepage rates of pairs giving similar estimates 

are difficult to accept. More repeat measurements should be 

conducted before accepting the estimates of flux using this 

method. In addition, measurements should be made every 4–6 

hours for several days to examine the response of seepage 

rates to diurnal variations in stream temperature and discharge 

resulting from evapotranspiration. 

Evapotranspiration losses attributed to stream 

evaporation, stream-bank evaporation, and transpiration 

from stream channel vegetation create diurnal discharge 

patterns that are characterized by decreasing stream 

discharge during the day, with minimum discharge generally 

occurring in the afternoon (Taylor and Nickle, 1936; 

Troxell, 1936a,b). The decrease in discharge results in 

increased temperature variations downstream. The traditional 

assumption that reduced afternoon discharge is due entirely to 

evapotranspiration losses (Penman, 1963; Wisler and Brater, 

1959) does not consider the importance of diurnal variations 

in stream temperature influencing seepage losses. A study 

conducted by Constantz and others (1994) demonstrates that 

for losing reaches with significant diurnal variations in stream 

temperature, the effect of stream temperature on streambed 

seepage is a major factor contributing to reduced streamflows. 

Studies using applied methods should incorporate quantitative 

analysis of diurnal stream–ground water interaction.
14 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Overall, the direct measurement technique as applied to 

this study resulted in inconclusive flux results. The moving 

streambed bottom seemed to be the limiting factor in applying 

this simple technique and overcame any other attempts to limit 

variability caused by the measurement technique. The seepage 

meters seemed to fail in this relatively high energy stream with 

its mobile bed. 

Laboratory Measurements

Laboratory Methods

The performance of the three types of collection bags 

used in this study was tested in a laboratory seepage tank to 

examine the effects of bag thickness on measured rates of 

vertical flux. A cylindrical test tank with an inside diameter 

and height of 152 cm contained a 91-cm thick layer (1.67 m3) 

of medium sand placed over a 15-cm layer (0.28 m3) wellsorted, rounded gravel, with a medium size of 1.9 cm (fig. 11). 

Vertical flux was generated within the tank by introducing 

a constant headwater source to the bottom of the tank, and 

flow was measured by an in-line flow meter. A data logger 

recorded both the flow rate delivered to the bottom of the tank 

and pressure head measured by a pressure transducer located 

in the constant head water source tank. The data logger was 

programmed to control the pump to maintain a constant water 

level. An overflow opening was used to maintain water level 

within the constant head source tank to within 0.15 cm inside 

the tank.

Sampling 

event

Field 

measurement 

period

Seepage 

meter 

array

Seepage 

meter size Bag type Objective

1 December 1–4, 2003 1 large shower bag Compare seepage rates between bag types and 

paired meters. small medical bag

2 January 28–29, 2004 1 large shower bag Compare measured rates using shower and medical 

bags in first 24-hour period to measured rates 

using only packaging bags in second 24-hr 

period.

small medical bag

January 29–30, 2004 1 large packaging bag

small packaging bag

3 February 10–11, 2004 1 large shower bag Compare measured rates using shower and medical 

bags in first 24-hour period to measured rates 

using only packaging bags in second 24-hr 

period.

small medical bag

February 11–12, 2004 1 large packaging bag

small packaging bag

4 July 20–21, 2004 2 large packaging bag

Compare measured rates between repeat 

measurements using same bag types and compare 

measured rates between seepage meters.

small packaging bag

July 21–22, 2004 2 large packaging bag

small packaging bag

5 September 21–22, 2004 2 large packaging bag

Compare measured rates between repeat 

measurements using same bag types and compare 

measured rates between seepage meters.

small packaging bag

September 22–23, 2004 2 large packaging bag

small packaging bag

6 September 22–23, 2004 2 large packaging bag

Compare measured rates between repeat 

measurements using same bag types and compare 

measured rates between seepage meters.

small packaging bag

September 23–24, 2004 2 large packaging bag

small packaging bag

Table 2. Objective and description of field measurements using seepage meters.

[Bag manufacturers: shower bag—Sun Solar Shower bag; medical bag—Medical Supply Bag; packaging bag—Void Packaging, Inc.]
Seepage Measurements 15

Streamflow direction

Figure 7. Scouring of streambed around seepage meter typically encountered 48 hours after deployment.

1 2 3 4 5 6

–0.6

–0.2

0.2

0

0.6

1.0

VERTICAL FLUX, IN CENTI

METERS PER DAY

VERTICAL FLUX, IN CENTI

METERS PER DAY

First 24-hr sampling

Second 24-hr sampling

Seepage meter A Seepage meter B

Seepage meter 1 Seepage meter 2

1 2 3 4 5 6

SAMPLING EVENT SAMPLING EVENT

–2

–1

0

1

1 2 3 4 5 6 –0.4

–0.2

0

0.2

0.4

0.6

1 2 3 4 5 6

–3

–2

–1

0

1

2

3

4

5

A

C

B

D

Figure 8. Measured vertical flux rates over consecutive 24-hour measurement periods for seepage meter pairs A-1 and B-2. 

A. Seepage meter A. B. Seepage meter B. C. Seepage meter 1. D. Seepage meter 2. (hr, hour.)
16 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Four seepage meters were placed in the test tank: two 

large and two small seepage meters. The system was allowed 

to equilibrate for 24 hours prior to the tests. The three types of 

collection bags used were the same as those used in the field 

(fig. 12). The wall thickness of each of the three collection 

bags was measured with vernier calipers at 0.41, 0.26, and 

0.04 mm, respectively. The collection bags were prefilled with 

a known volume of water and attached to the seepage meters 

using a 10-cm length of 0.64-cm-i.d. vinyl tubing. The seepage 

meters and connected bags were placed in the test tank for 60 

minutes for each test run. Seepage meters of the same crosssectional area were considered pairs for each test run. 

Two separate sets of tests were conducted. The objective 

of the first set of tests (tests 1 through 8) was to compare the 

results of measured vertical seepage rates with the known 

vertical test tank seepage rates. For these tests, a packaging 

bag and a medical bag were connected to the small seepage 

meters, and a packaging bag and shower bag were connected 

to the large seepage meters. At the end of a test, the collection 

bags were disconnected, weighed, and recorded. 

The second set of tests (tests 9–12) was conducted using 

only the packaging bags. The objective of these tests was to 

evaluate the ability of the collection bag to fill under various 

test scenarios. The vertical flux rate in the test tank was set to 

a known constant positive flux rate for the duration of all test 

runs conducted. The specifics for each of these test runs are 

presented in the Laboratory Results section.

Laboratory Results

A relative percent difference (RPD) was used to describe 

the variability between the measured vertical seepage rates and 

the known test tank vertical seepage rate for each of the 12 

tests. The RPD was calculated as the difference between the 

measured and known seepage rates divided by the average of 

the two values and is expressed as a percentage. An RPD of 

less than 10 percent between the known and measured seepage 

rates was considered acceptable for the tests conducted in the 

test tank. Table 3 lists the resulting variability for tests 1–8 in 

which the performance of the three different bag types was 

compared with the known test tank vertical flux. The median 

RPD for the shower bag connected to a large seepage meter 

was 121 percent, and the median RPD for the medical bag 

connected to small seepage meters was 96.5 percent. The 

median RPD for the packaging bags connected to the large and 

small seepage meters was 13.7 and 7.6 percent, respectively. 

The results of tests 1 through 8 are depicted as box plots in 

figure 13. 

1 2 3 4 5 6 –0.1

0.2

0

0.5

0.8

VERTICAL FLUX, IN CENTI

METERS PER DAY

VERTICAL FLUX, IN CENTI

METERS PER DAY

A Seepage meter C B Seepage meter D

C Seepage meter 3 D Seepage meter 4

1 2 3 4 5 6

–3

–1

1

0

3

5

1 2 3 4 5 6 –0.3

–0.1

0.1

0

0.3

0.5

1 2 3 4 5 6 –3

–2

–1

0

1

2

SAMPLING EVENT SAMPLING EVENT

First 24-hr sampling

Second 24-hr sampling

Figure 9. Measured vertical flux rates over consecutive 24-hour measurement periods for seepage meters pairs C-3 and D-4. 

A. Seepage meter C. B. Seepage meter D. C. Seepage meter 3. D. Seepage meter 4. (hr, hour.) 
Seepage Measurements 17

The results from tests 1 through 8 indicate that the 

thin-walled packaging bags performed better than the thickerwalled collection bags under an applied constant head. The 

thin-walled bags appear to be more compliant than the thickerwalled bags and filled easily. The compliance of bags to fill 

under an applied hydraulic head is affected by the size, shape, 

and the membrane thickness of the bag. The hydraulic head 

required to cause flow into the collection bags is expected to 

remain relatively constant until the bags fill with enough water 

to cause stretching, at which point the volumetric flow into the 

bag will decrease. Furthermore, if the membrane thickness of 

the collection bag is too large, the volumetric flow into a bag 

may reach a point where it rapidly decreases or ceases because 

the hydraulic head is not enough to overcome the resistance 

of the thicker-walled bag. Additional hydraulic head would be 

necessary to overcome the resistance and continue filling the 

bag. The high RPD for both the medical and shower bagsis 

likely a result of the latter, as the applied constant head during 

the test runs remained relatively constant throughout each test 

run, and the collection bags never filled to maximum capacity 

in any of the test runs. The volumetric flow rate that the flow 

meter measured at the beginning and end of each test run was 

recorded, and an RPD was calculated. The RPD between the 

flow rates at the beginning and end of each test run ranged 

from 0 to 7.6 percent for all tests (table 4).

In tests 9 through 12, compliance of the thin-walled 

packaging bags was tested under four different test scenarios 

(table 5). The results of test 9 indicate that the empty 

collection bag would fill if the tubing was filled; however, the 

RPD was twice the acceptable median RPD. Test runs 10 and 

11 compare the results starting with a partially filled collection 

bag and attaching the hose that is filled (test scenario 2) or 

empty (test scenario 3). In test scenario 3, it was unclear as 

to whether the applied constant head filled the tubing before 

flow into the bag occurred, or whether the initial volume that 

the bag contained filled the tubing to initiate flow into the 

collection bag. The median RPD for this test scenario was 

43.1 percent. The collection bags under test scenario 2 gave 

the best results. The results indicate that a small initial volume, 

void of any air bubbles or kinks in the collection bag or tubing, 

resulted in an average RPD between measured and known flux 

rates of 6.4 and 5.4 percent for the large and small seepage 

meters, respectively. 

1 2 3 4 5 6

–0.2

0

0

0.2

0.4

0.6

0.8

1 2 3 4 5 6

–3

–1

1

3

5

1 2 3 4 5 6

–0.5

–0.3

–0.1

0.1

0.3

0.5

1 2 3 4 5 6

–2

–1

0

0

1

C Seepage meter 5 D Seepage meter 6

A Seepage meter E B Seepage meter F

First 24-hr sampling

Second 24-hr sampling

VERTICAL FLUX, IN CENTI

METERS PER DAY

VERTICAL FLUX, IN CENTI

METERS PER DAY

SAMPLING EVENT SAMPLING EVENT

Figure 10. Measured vertical flux rates over consecutive 24-hour measurement periods for seepage meter pairs E-5 and F-6. 

A. Seepage meter E. B. Seepage meter F. C. Seepage meter 5. D. Seepage meter 6. (hr, hour.) 
18 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Datalogger

Overflow opening to 

maintain constant 

water level

Pump

Basin

In-line

flow meter

152-cm diameter by 

152-cm high poly tank Seepage

meter

2.5-cm diameter 

PVC pipe

Adjustable 

constant head

water source

Pressure

transducer

91-cm layer of sand

Regularly spaced

holes in 1.3-cm

thick PVC sheet

Water outlet into tank — four slotted, 2-cm diameter PVC pipes

15-cm layer

of gravel

5-cm diameter 

PVC pipe (not to scale)

collection bag

Figure 11. Laboratory test tank setup used for testing of different types of collection bags attached to seepage meters. 

Test tank setup and design by Michael Menheer in 2004, U.S. Geological Survey (cm, centimeter; PVC, polyvinyl chloride).

A B C

Figure 12. Seepage meter collection bag types. A. Sun Shower Solar Bag. B. medical supply bag. C. Void-Fill packaging bag.
Seepage Measurements 19

The results of test run 12, in which empty tubing and an 

empty collection bag were attached to the seepage meters, 

indicate that the RPD between the known and measured 

vertical flux rate was much greater than the acceptable 

difference. The high RPD (median RPD of 90.3 percent) for 

this test scenario appears to be related to the energy required 

to open a bag that is initially empty. Other investigators 

(Erickson, 1981; Shaw and Prepas, 1990a,b; Belanger and 

Montgomery, 1992; Landon and others, 2001) have reported 

problems with seepage meter performance when using bags 

that were initially empty. 

Overall, the laboratory results of the three bag types 

tested indicate that the thin compliant packaging bags 

performed better than the medical and shower bag under 

the applied laboratory conditions. In addition, results of test 

runs 9–12 indicate that the packaging bags performed best 

when started with an initial volume and filled tubing prior to 

attachment to seepage meters (test scenario 2). Results of each 

of the test scenarios summarized in table 5 are depicted in 

figure 14.

Test 

number Seepage meter Bag type

Measured vertical 

flux rate 

(cm/day)

Known test tank 

vertical flux 

(cm/day)

Relative percent 

difference

1 Large seepage meter shower bag 3.45 17.1 133

Large seepage meter packaging bag setup problem 17.1 NA

Small seepage meter packaging bag 18.5 17.1 7.66

Small seepage meter medical bag 11.6 17.1 38.4

2 Large seepage meter shower bag 2.97 16.8 140

Large seepage meter packaging bag 14.6 16.8 13.7

Small seepage meter packaging bag 16.3 16.8 3.02

Small seepage meter medical bag 5.65 16.8 99.1

3 Large seepage meter shower bag 4.88 19.0 118

Large seepage meter packaging bag 16.4 19.0 14.4

Small seepage meter packaging bag 17.7 19.0 6.81

Small seepage meter medical bag 5.46 19.0 111

4 Large seepage meter shower bag 3.83 17.1 127

Large seepage meter packaging bag 15.1 17.1 12.8

Small seepage meter packaging bag 15.7 17.1 8.38

Small seepage meter medical bag 1.56 17.1 167

5 Large seepage meter shower bag 2.57 17.1 148

Large seepage meter packaging bag 14.5 17.1 16.6

Small seepage meter packaging bag 18.5 17.1 7.46

Small seepage meter medical bag 4.19 17.1 121

6 Large seepage meter shower bag 7.18 17.5 83.6

Large seepage meter packaging bag 18.5 17.5 5.34

Small seepage meter packaging bag 15.9 17.5 9.54

Small seepage meter medical bag 10.2 17.5 52.6

7 Large seepage meter shower bag 4.02 5.21 35.5

Large seepage meter packaging bag 5.65 5.21 25.7

Small seepage meter packaging bag 5.69 5.21 8.85

Small seepage meter medical bag 11.2 5.21 72.9

8 Large seepage meter shower bag 2.42 5.58 79.0

Large seepage meter packaging bag 5.06 5.58 9.76

Small seepage meter packaging bag 6.00 5.58 7.23

Small seepage meter medical bag 1.95 5.58 96.5

Table 3. Results of measured and known vertical flux rates, including relative percent difference, for collection bag types.

[cm, centimeter; NA; not applicable]
20 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Laboratory results suggested that use of thin-walled 

collection bags would provide the best seepage meter results 

for obtaining streambed fluxes. Following laboratory tests, 

thin-walled bags were exclusively used as collection bags in 

the field. All bags were filled with approximately 500 or 1,000 

mL of water. The bags were connected to seepage meters with 

filled tubing, and the water in the bags was void of any air 

bubbles. 

RELATIVE PERCENT DIFFERENCE

Small seepage meter and

 medical bag

Small seepage meter and

 packaging bag

Large seepage meter and

 shower bag

Large seepage meter and

 packaging bag

0

50

100

150

200

n = 8 n = 8 n = 8 n = 7

highest RPD

75th percentile

median

25th percentile

lowest RPD

NUMBER OF VALUES

Figure 13. Boxplots of relative percent difference between measured and known seepage rates. (RPD, relative percent difference.)
Seepage Measurements 21

Test 

number

Tank flux rate 

at start of test 

(mL/min) 

Tank flux rate at 

end of test 

(mL/min) 

Percent 

difference

1 219 223 2.2

2 214 209 2.2

3 242 233 3.9

4 219 219 0.3

5 219 204 6.5

6 223 233 4.3

7 66.5 67.2 1.1

8 71.3 71.4 0.1

9 233 233 0.0

10 233 233 0.0

11 61.7 57.0 7.6

12 66.5 68.2 2.6

Test 

number

Seepage 

meter

Test scenario

 description

Test 

scenario 

Measured 

vertical 

flux rate 

(cm/day)

Known test 

tank vertical 

flux (cm/day)

Percent 

difference

9 Large 0 initial volume, tubing filled 1 23.0 18.2 26.4

Large 0 initial volume, tubing filled 1 22.5 18.2 23.6

Small 0 initial volume, tubing filled 1 15.2 18.2 16.5

Small 0 initial volume, tubing filled 1 15.1 18.2 17.0

10 Large 50 mL initial volume, tubing filled 2 19.5 18.2 7.1

Large 50 mL initial volume, tubing not filled 3 21.4 18.2 17.6

Small 50 mL initial volume, tubing filled 2 16.7 18.2 8.2

Small 50 mL initial volume, tubing not filled 3 11.6 18.2 36.3

11 Large 50 mL initial volume, tubing filled 2 4.5 4.8 6.3

Large 50 mL initial volume, tubing not filled 3 7.4 4.8 54.2

Small 50 mL initial volume, tubing filled 2 4.9 4.8 2.1

Small 50 mL initial volume, tubing not filled 3 1.8 4.8 62.5

12 Large 0 initial volume, empty tubing 4 13.8 5.2 165

Large 0 initial volume, empty tubing 4 13.9 5.2 167

Small 0 initial volume, empty tubing 4 1.9 5.2 63.5

Small 0 initial volume, empty tubing 4 2.5 5.2 51.9

Table 4. Comparison of test tank flux rate at beginning and end 

of each test run.

[mL/min, milliliter per minute]

Table 5. Results of test scenarios using thin-walled packaging collection bags.

[cm, centimeter; mL, milliliter] 
22 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Estimates of Streambed Hydraulic 

Conductivity

Streambed hydraulic conductivity was estimated using 

grain-size analyses and slug tests. Although slug tests measure 

hydraulic conductivity values that depend on horizontal 

and vertical flow, and hydraulic conductivity values from 

grain-size methods are nondirectional, the two methods are 

directly compared for the purpose of characterizing streambed 

hydraulic conductivity.

Methods

Grain-Size Analysis

A total of six sediment cores were collected from near 

each of the in-stream monitoring well pairs depicted in 

figure 15, and sieve test analysis was conducted on each core. 

The cores were collected at the sediment–water interface, 

and the length of collected cores ranged from 25 to 46 cm. 

Core samples consisted of a homogeneous medium-to-coarse 

grained, well-sorted sand. The weight percent from each sieve 

size class was used to calculate a cumulative weight percent, 

and a grain-size distribution curve was generated for each 

core collected. The resulting curves depicted in figure 16

Empty bag with

 filled tubing

Partially filled bag

 with filled tubing

Partially filled bag

 with empty tubing

Empty bag with 

 empty tubing

0

50

100

150

200

n = 4 n = 4 n = 4 n = 4

NUMBER OF VALUES

highest RPD

75th percentile

median

25th percentile

lowest RPD

RELATIVE PERCENT DIFFERENCE

Figure 14. Boxplots of relative percent difference of bag compliance under various test scenarios. 

(RPD, relative percent difference.)
Estimates of Streambed Hydraulic Conductivity 23

represent the grain-size distribution curves for the samples 

collected at the upstream and downstream transects. These 

curves were used to approximate the hydraulic conductivity 

of the streambed sediments by the Hazen approximation. This 

method is applicable to sands where the effective grain size is 

between approximately 0.1 and 3.0 mm.

Hazen Approximation

 Grain-size distribution curves can be used to estimate 

the hydraulic conductivity of sands where the effective grain 

size is between approximately 0.1 to 3.0 mm (Fetter, 2001) 

by applying the Hazen method (Hazen, 1911). The effective 

grain size, d10, is the size corresponding to the 10 percent line 

on the grain-size distribution curve and represents passing 

of 10 percent finer (by weight) of the sample during the 

sieve analysis. These values from the generated grain-size 

distribution curves were applied to the Hazen approximation 

for hydraulic conductivity as follows:

K = C × (d )

where:

K = hydraulic conductivity (cm/s)

d = eff

10

2

10 eective grain size (cm/s)

C = coefficient based on grain size(Fetter, 2001) (1)

15

20

25

30

ELEVATION, IN METERS ELEVATION, IN METERS

Right bank, north 

BW-052

BW-051

BW-016

BW-017

RW-043

RW-044

RW-034

RW-035 RW-026

RW-025

15

20

25

30

0 10 20 30 40 50

HORIZONTAL DISTANCE, IN METERS

0 10 20 30 40 50

HORIZONTAL DISTANCE, IN METERS

Right bank, north Left bank, south

RW-098

RW-099 RW-090

RW-089

RW-0081

RW-080

BW-071

RW-072

BW-106

BW-107

Left bank, south

B Transect 1 (downstream transect)

A Transect 2 (upstream transect)

water level water level

water level water level

stream bed and 

land surface

stream bed and 

land surface

Figure 15. Cross-sectional schematic of monitoring well name and location for the upstream and downstream transects.

A. Upstream. B. Downstream. (BW, bank well; RW, river well.) 
24 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Slug Tests

Slug tests were performed on 18 of the 20 monitoring 

wells located at the study site on September 20 and 21, 2004. 

Eight of the slug tests were performed on the riparian bank 

monitoring wells screened at approximately 3.5 and 5 m 

below land surface, and 10 were performed on the in-stream 

monitoring wells screened at approximately 0.5 and 3 m 

below the sediment–water interface. Two different slugs 

were used; both were made of out of PVC plastic tubing, 

filled with sand, capped and sealed (dimensions: 45.7 cm 

by 3.2 cm and 91.4 cm by 3.2 cm, or 1.5 ft by 1.25 in. and 

3 ft by 1.25 in.). The larger slug was used in the monitoring 

wells that were screened at greater depths, and the smaller 

slug was used in the monitoring wells that were screened at 

shallow depths. Aquistar PT2X pressure transducers were 

used to measure and record the head changes during these 

slug tests. The transducers were set to record at 0.1-second 

intervals and allowed to equilibrate with the well before the 

slug was dropped or removed. The recovery time for each 

Figure 16. Grain-size distribution curves for sediment cores collected at the upstream and downstream transects.

A. Upstream. B. Downstream. (RW, river well.)

0

20

40

60

80

100

120

0.0001 0.001 0.01 0.1 1 10 100

RW-025

RW-034

RW-043

0

20

40

60

80

100

120

0.0001 0.001 0.01 0.1 1 10 100

RW-080

Sites:

Sites:

RW-089

RW-098

GRAIN SIZE, IN MILLIMETERS

GRAIN SIZE, IN MILLIMETERS

PERCENT FINER BY WEIGHT PERCENT FINER BY WEIGHT

A Grain-size distribution curve transect 2 (upstream transect)

B Grain-size distribution curve transect 1 (downstream transect)
Estimates of Streambed Hydraulic Conductivity 25

individual slug test ranged from seconds to minutes, and only 

one monitoring well (BW-016) did not fully recover between 

tests. This well was screened in a silty-clay layer. Figure 17

depicts the typical recovery time and fit of data for estimating 

hydraulic conductivity.

The Bouwer and Rice (1976) application was used from 

the AQTESOLV software program to estimate hydraulic 

conductivity from slug tests. The collected water-level 

displacement data for each set of slug tests input into the 

program included only the data beginning with the maximum 

displacement of water level and assigned time zero. The form 

factor that AQTESOLV applies to the Bouwer and Rice (1976) 

solution for an unconfined aquifer assumes the form factor 

described in Fetter (2001). 

Results

The calculated hydraulic conductivity results of the 

applied grain-size analysis and slug test method were 

compared. During low-flow conditions, sediment core 

samples were collected in August 2004, and slug tests were 

conducted in September 2004. Sediment core samples used to 

determine hydraulic conductivity were approximately 25–46 

cm in length, and therefore, could be compared with slug 

tests performed in the shallow in-stream monitoring wells 

screened at approximately 0.5 m below the sediment–water 

interface. Estimates of hydraulic conductivity for bank wells 

are by slug test only, as sediment core samples were not 

collected for these sites. Tables 6 and 7 present the results of 

applied methods for the upstream and downstream transects, 

respectively. 

RW-044 — OUTPUT FROM AQTESOLVE

0 8 16 24 32 40

0.01

0.1

1

10

TIME, IN SECONDS

DISPLACEMENT, IN FEET

2.2

2.3

2.4

2.5

2.6

2.7

2.8

47:31 47:48 48:06 48:23 48:40

RW-044 (RAW DATA)

PRESSURE HEAD, IN FEET

TIME ELAPSED, IN SECONDS

Obs. Wells

 RW-044

Aquifer Model

 Unconfined

Solution

 Bouwer-Rice

Parameters

 K = 49.36 m/day

 y0

 = 1.239 ft

Figure 17. Example of typical recovery time and fit of data for estimating hydraulic conductivity by slug test. 

(ft, feet; K, hydraulic conductivity; m, meter; Obs., observed; RW, river well.)
26 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

USGS 

site ID

number

Monitoring 

well ID 

number

Location and type Depth

Method of 

hydraulic 

conductivity 

estimate

Measured 

hydraulic 

conductivity 

(m/day)

372312120481106 BW-106 Bank monitoring well, north bank shallow Bouwer and Rice, 1976 80

372312120481107 BW-107 Bank monitoring well, north bank deep Bouwer and Rice, 1976 60

372312120481098 RW-098 River monitoring well, river right shallow Bouwer and Rice, 1976 120

Hazen, 1911 110

372312120481099 RW-099 River monitoring well, river right deep no slug test no slug test

372312120481089 RW-089 River monitoring well, middle shallow Bouwer and Rice, 1976 50

Hazen, 1911 50

372312120481090 RW-090 River monitoring well, middle deep Bouwer and Rice, 1976 250

372312120481080 RW-080 River monitoring well, river left shallow Bouwer and Rice, 1976 50

Hazen, 1911 50

372312120481081 RW-081 River monitoring well, river left deep Bouwer and Rice, 1976 60

372312120481071 BW-071 Bank monitoring well, south bank shallow Bouwer and Rice, 1976 40

372312120481072 BW-072 Bank monitoring well, south bank deep Bouwer and Rice, 1976 40

USGS 

site ID

number

Monitoring 

well ID 

number

Location and type Depth

Method of 

hydraulic 

conductivity 

estimate

Measured 

hydraulic 

conductivity 

(m/day)

372312120481051 BW-051 Bank monitoring well, north bank shallow Bouwer and Rice, 1976 60

372312120481052 BW-052 Bank monitoring well, north bank deep Bouwer and Rice, 1976 70

372312120481043 RW-043 River monitoring well, river right shallow Bouwer and Rice, 1976 100

Hazen, 1911 20

372312120481044 RW-044 River monitoring well, river right deep Bouwer and Rice, 1976 50

372312120481034 RW-034 River monitoring well, middle shallow Bouwer and Rice, 1976 30

Hazen, 1911 70

372312120481035 RW-035 River monitoring well, middle deep Bouwer and Rice, 1976 20

372312120481025 RW-025 River monitoring well, river left shallow Bouwer and Rice, 1976 no slug test

Hazen, 1911 70

372312120481026 RW-026 River monitoring well, river left deep Bouwer and Rice, 1976 40

372312120481016 BW-016 Bank monitoring well, south bank shallow Bouwer and Rice, 1976 10

372312120481017 BW-017 Bank monitoring well, south bank deep Bouwer and Rice, 1976 80

The estimated hydraulic conductivity for the upstream 

transect by slug test ranged from 40 to 250 m/day, whereas 

that for the downstream transect ranged from 10 to 100 

m/day. A relative percent difference (RPD) was used to 

describe the variability in estimates of hydraulic conductivity 

by grain-size analysis and slug test. Variability in applied 

methods at the upstream transect ranged from 0 to 9 percent, 

in which both RW-089 and RW-080 resulted in estimated 

hydraulic conductivities of 50 m/day. Estimates of hydraulic 

conductivity for the downstream transect showed greater 

variability, with a range of 80 to 133 percent between applied 

methods. Location of screened interval likely explains 

variability in range of estimates. BW-016 was screened in a 

silty-clay layer, and pebbles and cobbles were encountered 

during the installation of the in-stream wells RW-098 and 

RW-090. The sieve test analysis and slug tests were conducted 

within one month of each other, and therefore, represent a 

“snapshot” of hydraulic conductivity during 2004 summer 

low-flow conditions. 

Table 6. Estimated hydraulic conductivity by slug test and (or) grain-size analysis at upstream transect (transect 2).

[Bouwer and Rice = slug test method; Hazen = grain-size method. BW, blank well; ID, identification; m, meter; RW, river well]

Table 7. Estimated hydraulic conductivity by slug test and (or) grain-size analysis at downstream transect (transect 1).

[Bouwer and Rice = slug test method; Hazen = grain-size method. BW, blank well; ID, identification; m, meter; RW, river well]
Estimating Seepage Using Heat as a Tracer 27

Estimating Seepage Using Heat as a 

Tracer

Temperature is a controlling variable for aquatic life in 

the water column and in streambed sediments. Exchanges 

that occur between streams and ground-water systems play 

a key role in controlling temperatures not only in the stream, 

but also in the underlying sediments. Heat is transported 

through stream sediments by advection and conduction where 

temperature differences exist. Heat as a tracer is a simple 

yet powerful tool for detecting water movement across the 

sw–gw interface when this movement is traced by continuous 

monitoring of temperature patterns in the streambed and 

subsurface water. 

The use of heat as a hydrologic tracer has several 

distinct advantages over applied chemical tracers. The 

temperature signal occurs naturally, rather than having to be 

introduced into the stream setting. The primary measurement 

is temperature, which is robust and a relatively inexpensive 

parameter to measure. In contrast to chemical tracers, which 

often require laboratory analysis before interpretation, 

temperature data are immediately available for inspection 

and interpretation (Stonestrom and Constantz, 2003). As a 

result, analyses of subsurface temperature patterns provide 

information about sw–gw interactions.

Streams exhibit diurnal temperature fluctuations as 

a result of solar-driven temperature fluctuations at the 

land surface, whereas ground water is buffered from these 

temperature fluctuations below the surface. The difference 

in temperature between streams and ground water provides 

a means for tracing exchanges between the two systems. In 

a gaining reach of a river, water is moving upward into the 

streambed and carries with it the relatively static temperature 

signal of the ground water. As a result, the temperatures in and 

beneath the gaining reach are muted compared with the diurnal 

fluctuations in the stream. Conversely, if the stream is losing 

water volume by seeping down through riverbed to ground 

water, and water is moving downward into the streambed, the 

diurnal temperature signal of the river is carried by advection 

and conduction into the surrounding sediments. Subsurface 

temperature patterns will exhibit the diurnal fluctuations seen 

in the stream. Figure 18 depicts these concepts. 

Review of Literature

Heat has been used as a tracer of subsurface water 

movement for more than 40 years. Analytical solutions to 

equations that govern the coupled movement of water and heat 

have been derived and applied to estimate the rate at which 

water travels from the surface to great depths (Rorabaugh, 

1954; Stallman, 1963). Temperature patterns have also been 

used to study subsurface flow systems ranging from irrigation 

water in rice paddies to geothermal water beneath volcanoes 

(Suzuki, 1960; Sorey, 1971). Lapham (1989) used annual 

temperature records from deep observation wells to identify 

rates of vertical water flux in several streams in Massachusetts 

and New Jersey that were based on analytical solutions 

reported in earlier work (Lapham, 1988). However, these 

analytical solutions were derived for a few idealized cases 

and resulted in theoretical, rather than practical, applications 

because of measurement and computational limitations. 

Recently, the measurement and modeling of heat and water 

transport have benefited from significant improvements. 

Recent innovations in sensor and data-acquisition technology, 

along with substantial improvements in numerical modeling, 

present new opportunities for the use of heat as a tracer of 

stream–ground water exchanges (Stonestrom and Constantz, 

2004). Inexpensive and accurate devices are now available for 

measuring temperature, water level, and water content. These 

devices, in conjunction with currently available numerical 

models, provide general solutions of equations for the coupled 

transport of heat and water.

Sw–gw exchanges can be estimated using heat as a tracer 

in conjunction with water level measurements (Silliman and 

Booth, 1993; Silliman and others, 1995; Stonestrom and 

Constantz, 2003; Anderson, 2005). Temperature has been used 

as a tracer to identify vertical flux across the sw–gw interface 

at various locations in the United States. In the Rio Grande 

near Albuquerque, New Mexico, Bartolino and Niswonger 

(1999) used the USGS numerical model (VS2DH) to match 

simulated temperature data to observed temperature, yielding 

predicted estimates of deep streambed fluxes and spatially 

averaged hydraulic conductivities. Application of heat as a 

tracer has been used to examine interactions in alpine streams 

between stream temperature, streamflow, and ground-water 

exchanges (Constantz, 1998). The analysis of temperature 

profiles in ephemeral stream environments has been used 

to examine percolation characteristics beneath arroyos in 

the Middle Rio Grande Basin, New Mexico (Constantz and 

Thomas, 1997), to determine streamflow frequency and 

duration (Constantz and others, 2001), and to investigate 

stream losses beneath ephemeral channels (Constantz and 

others, 2002). Stonestrom and Constantz (2003) provide 

technical details of the use of heat as an environmental tracer 

as well as a compilation of seven detailed case studies that use 

temperature patterns and their interpretation as a hydrologic 

tool for the assessment of interactions between surface water 

and ground water in a variety of environmental settings 

throughout the western United States. 
28 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Sampling Design and Methodology

The study site location on the lower Merced River was 

selected because the reach was within the study area that 

encompassed the overall USGS’s NAWQA agricultural 

chemical transport (ACT) study design and objectives. To 

understand how agricultural chemicals move through and 

between hydrologic compartments (atmosphere, surface 

water, the unsaturated zone, ground water, and sw–gw 

interaction), a gaining reach of river was preferable for the 

sw–gw component. Reconnaissance of the reach indicated 

that the reach was gaining and easily accessible for sampling 

equipment installation and subsequent sampling events. In 

addition, agricultural chemicals of interest were being applied 

to crops north and south of the selected reach.

A total of twenty 5-cm (2 in.) polyvinyl chloride (PVC) 

screened monitoring wells were installed across two transects 

in the Merced River. Transects were separated by a distance 

of approximately 100 m. Each transect was equipped with 

five pairs of monitoring wells: three pairs in the river and a 

pair on the right and left banks in the riparian zone. Figure 19

depicts a bank and in-stream monitoring well pair. The pairs of 

monitoring wells at each transect consisted of a shallow and a 

deep monitoring well screened at approximately 0.5 and 3 m 

below the streambed for the in-stream monitoring wells, and at 

approximately 3.5 and 5.0 m below the top of well casing for 

the riparian zone monitoring wells. The monitoring wells were 

equipped with temperature loggers and pressure transducers. 

Figure 20 depicts a cross-sectional view of an equipped 

transect. 

Temperature loggers monitored temperature continuously 

in both the surface water (above the sediment–water interface) 

and at three depths within the streambed at both transects. 

Pressure transducers located in the stream and below the 

streambed collected water-level data that were used to 

define boundary conditions. Temperature and pressure-head 

data were input into the USGS numerical model, Variably 

Saturated 2-Dimensional Heat (VS2DH; Healy and Ronan, 

1996) and its graphical interface VS2DI (Hsieh and others, 

2000). This program uses an energy transport approach via 

the advection–dispersion equation to simulate heat and flow 

transport. Estimates of streambed hydraulic and thermal 

conductivity were input into the model until model simulations 

“fit” observed subsurface streambed temperatures. This 

inverse modeling method uses a visual best fit and is most 

sensitive to variations in the input parameter K (hydraulic 

conductivity).

The monitoring wells were installed by pumping the 

streambed sediment out while pushing in a 15-cm (6 in.) 

diameter PVC casing downward to the desired depth. After 

reaching the desired depth, the smaller 5-cm (2 in.) PVC 

monitoring well was inserted inside the 15-cm PVC casing, 

and the 15-cm casing was pulled out of the streambed, 

allowing the surrounding streambed sediments to collapse 

around the 5-cm PVC monitoring well. The streambed 

monitoring wells were installed so that the top of the casing 

of each of the wells was slightly above the streambed. Once 

in place, the monitoring wells were sealed with standard 

pressurized monitoring well caps to prevent stream water from 

entering the monitoring wells. The same installation procedure 

was used for the riparian zone monitoring wells; however, a 

combination of hand augering and pumping was used to install 

the outer casing to the desired depth. A Monterey sand pack 

was placed around the screened interval of each of the riparian 

zone monitoring wells. The wells were then sealed with a 

bentonite cap and backfilled to land surface. Convection in 

the riparian zone wells was not of concern because convection 

does not occur in small-diameter wells under saturated 

conditions or in the absence of large temperature gradients 

between temperature probes, as confirmed by reconnaissance 

and collected data.

GAINING REACH

LOSING REACH

TIME

STREAM

GAGE

TIME

FLOW

TEMPERATURE

TIME

TEMPERATURE

water level

TIME

STREAM

GAGE FLOW

water level

A

B

Figure 18. Streamflow and temperature histories for gaining 

and losing reaches of a stream coupled to the local ground-water 

system. Ground water is buffered from temperature fluctuations 

at the land surface. A., temperature fluctuations in and beneath 

the gaining reach are therefore muted (top panel) compared with 

B., temperatures in and beneath the losing reach (bottom panel). 

Modified with permission from Stonestrom and Constantz, 2004.
Estimating Seepage Using Heat as a Tracer 29

A string of three HOBO Water Temp Pro temperature 

loggers (accuracy: ±0.2°C at 0 to 50°C range) was fastened 

to a small diameter rope at depths of approximately 0.5, 

1.0, and 2.0 m from the monitoring well cap (fig. 21). These 

depths were chosen because during reconnaissance of the 

site, static ground-water temperatures were encountered at 

approximately 2.5 m below the sediment–water interface. 

The temperature loggers were then weighted with a stainlesssteel bolt and placed in each of the deep in-stream monitoring 

wells. The same procedure was used for the riparian zone 

monitoring wells; however, the temperature loggers were 

placed at approximately 3.5, 4.0, and 5.0 m below the top of 

the monitoring well casing. These depths were chosen because 

the water table was approximately 3 m below land surface. 

A temperature logger was also placed in the stream to record 

stream temperature. A total of 10 pressure transducers were 

used to record water levels: eight in four pairs of the in-stream 

monitoring wells, one in the deep riparian monitoring well at 

the downstream transect, and one in the Merced River.

Temperature and pressure were measured at 15-minute 

intervals. Manual water level measurements were also taken 

through the study in the riparian zone monitoring wells and 

during data downloads for the in-stream monitoring wells. 

Because the top of the casing for the in-stream monitoring 

wells was underwater (approximately 5–10 cm above the 

streambed), a 1.8-m riser was attached to the in-stream 

monitoring well and allowed to equilibrate prior to water level 

measurements. Table 8 identifies the wells by name, location, 

and the type of continuous data (temperature and [or] pressure 

head) recorded in each of the monitoring wells.

A B

Figure 19. Bank and in-stream monitoring well pair at downstream transect. A. Bank. B. In-stream. The center rectangular object is a 

cover for the tubing that was used to sample wells.
30 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Results

In this study, the application of temperature as a tracer 

utilized continuous monitoring of water levels, and subsurface 

temperature, as well as the elevation and temperature of the 

stream. Data were used to specify the boundary conditions 

in the numerical model VS2DH, and estimates of hydraulic 

and thermal conductivity were adjusted in the model until 

“best fit” simulations matched the observed subsurface stream 

temperatures at intermediate depth. This method requires 

high precision in the water-level data and certainty in the 

elevations (depths) at which the pressure transducers are 

placed at. However, because of problems associated with 

the instrumentation used to record continuous water-level 

elevation, prolonged unexpected high streamflow events, and 

the resulting scour and burial of the monitoring wells, the 

results of the recorded total-head distributions and temperature 

profiles are discussed prior to the modeling results, as these 

results affect the final model results. Furthermore, results 

and discussion of total-head distributions and collected 

temperature data for monitoring wells at the upstream transect 

are not presented because of vandalism and scour.

Total-Head Distributions

Total hydraulic head (meters) is defined as the recorded 

pressure head plus the known elevation at which each of the 

pressure transducers was placed. A pressure transducer was 

placed in the river to record continuous stream elevation 

data. These recorded stream elevations were used to calculate 

differences in total head between the ground water and the 

river, thereby indicating the direction of flow across the 

sediment–water interface at the instrumented site. Gaining 

and losing reaches were defined from the perspective of the 

river, which is standard protocol. Specifically, a positive 

value indicates a gaining reach and a negative value indicates 

a losing reach. However, in the present study, the pressure 

transducer placed in the river did not provide the quality 

of data that the instrument was intended to record for 

several reasons. The initial study design included a plan for 

differences in head between the river and ground water on a 

very small scale (1–3 cm). Unfortunately, the inherent error 

associated with the estimated elevation of the location of the 

pressure transducer placed in the Merced River was greater 

than the measured head differences between the surface water 

and ground water. This problem was further complicated with 

each download of data; when the pressure transducer was 

removed and downloaded, it was nearly impossible to replace 

the instrument at an exact height in the well. In addition, 

H

s

i

e

h

,

P

.

A

H

s

i

e

h

,

P

.

A

.

,

H

s

i

e

h

RIGHT BANK, NORTH LEFT BANK, SOUTH

Pressure transducer

Temperature logger

 (not to scale)

water level

5 m

3.5 m 0.5 m

3 m

Figure 20. Cross-sectional view of instrumented transect. (m, meter.) 
Estimating Seepage Using Heat as a Tracer 31

the PVC casing that housed the pressure transducer was at 

approximately a 40o angle from horizontal, and it was difficult 

to replace the instrument at its intended location because it 

was not free-hanging under gravity.

Pressure transducers located below the streambed in the 

paired monitoring wells screened below the streambed did 

not have these limitations. These pressure transducers were 

attached to the cap of the monitoring wells and allowed to 

hang freely within the monitoring well. Manual water-level 

measurements taken immediately after data downloads agreed 

well with recorded water levels to within <0.3 cm. As a result, 

the paired in-stream monitoring wells (MW) (delta H = deep 

MW – shallow MW) were used to calculate head differences.

Although the pressure head recorded in each of the 

streambed monitoring wells agreed with manual measurements, the minor discrepancy between the recorded water 

level and measured water level seemed to increase in the latter 

part of the study, suggesting drift in the pressure transducers. 

The pressure transducers used in this study were not vented 

to the atmosphere and were placed in monitoring wells that 

were sealed at the streambed. As a result, this type of pressure 

transducer requires an additional pressure transducer 

(baro-logger) to record and compensate for changes in 

atmospheric pressure. The data collected from the baro-logger 

were subtracted from the recorded head data collected in the 

monitoring wells. The atmospheric pressure and water levels 

calculated by the baro-logger and the pressure transducers 

are temperature compensated, though large changes in 

temperature over a short period can affect how the instrument 

calculates water pressure (Davies, 2002). 

Figure 22 depicts discharge and recorded head 

differences (delta H) between the deep and shallow monitoring 

wells at the downstream transect. Mean daily discharge 

data is obtained from the Department of Water Resources 

stream gaging station, Merced River near Stevinson (site ID 

11272500), approximately 16 mi upstream from the study 

area. An 18-hour travel time was determined and applied 

using a travel-time equation from Kratzer and Biagtan (1997). 

The pressure transducer malfunctioned after the September 

2004 download in monitoring well pair RW-044 and RW-043 

(fig. 22A). Head differences for monitoring well pair RW035 

and RW034 (fig. 22B) recorded a generally gaining river 

throughout the study period with distinct flow reversals 

(gaining to losing) during high streamflow events. These 

A B

Figure 21. Measurement of spacing for temperature loggers placed in in-stream well and placement of temperature loggers in riparian 

bank well. A. In-stream well. B. Riparian bank well.
32 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

flow reversals correspond to storm events during winter 

months, relatively large releases at the New Exchequer Dam 

to improve downstream salmon habitat from mid-April to 

mid-May, and smaller releases made in October as part of the 

Vernalis Adaptive Management Plan (VAMP). The waterlevel data collected from the monitoring well pair RW044 and 

RW043 (fig. 22A) did not record a flow reversal across the 

sediment–water interface during the May 2004 VAMP release. 

Agricultural fields upgradient of the transects are 

irrigated between March and September, which seasonally 

recharges the surficial aquifer. The rise in water levels of 

the surrounding aquifer is reflected in the water levels of the 

monitoring well pairs, indicating a gaining stream during 

irrigation season 2004. Irrigation season 2005 did not result in 

gaining conditions because of large streamflow releases from 

New Exchequer Dam beginning March 2005 and continuing 

through the end of the study period. These releases were made 

as a result of spring melt of an exceptionally high snowpack in 

the upper part of the basin. 

Temperature Profiles

During the winter months, the stream temperature 

becomes much cooler than recorded subsurface temperatures, 

and conversely during the summer months, the stream 

temperature becomes much warmer. Figure 23 depicts daily 

average temperature profiles collected at the downstream 

transect. The in-stream monitoring wells recorded nearly the 

same temperature patterns at 0.5, 1.0, and 2.0 m below the 

streambed. Periods of gaining or losing are recorded, and 

in general, the subsurface temperatures indicate a slightly 

gaining-to-neutral reach throughout 2004, with the exception 

of mid-April to mid-May 2004 during the VAMP flow events 

when the temperature record indicated a losing scenario.

Temperature records from 2005 coincide with the 

exceptionally high streamflow. This likely caused scour 

around the in-stream monitoring wells during the rising limb 

of the hydrograph and subsequent burial during the falling 

limb. Field observations support this assumption. As a result, 

significant uncertainty was created with respect to depth of 

recorded temperature variations. Despite this concern, the 

collected temperature data for this time period indicates a 

losing-stream scenario until June 2005, after which a strongly 

gaining-stream time period is recorded. Stream elevation 

approached and overtook bank well BW017 during the spring 

2005 dam release and was in direct contact with the river and 

recorded stream temperature.

The bank wells follow the same temperature patterns as 

the in-stream wells, but to a much lesser extent. During the 

summer months, ground-water temperatures at 3.5 m were 

warmer than those recorded at 5 m, and conversely, during the 

winter months, recorded temperatures at 5 m were warmer 

than those at 3.5 m. These changes occurred in June and 

November, respectively. The bank wells do not record diurnal 

temperature variations (fig. 24), but do record slight seasonal 

changes.

USGS 

site ID

number

Monitoring 

well number

Screened 

depth 

(meters)

Transect Equipment1

372312120481106 BW-106 3.5 upstream, transect 2 none

372312120481107 BW-107 5 upstream, transect 2 temperature loggers

372312120481098 RW-098 0.5 upstream, transect 2 pressure transducer

372312120481099 RW-099 3 upstream, transect 2 temperature loggers and pressure transducer

372312120481090 RW-090 0.5 upstream, transect 2 pressure transducer

372312120481089 RW-089 3 upstream, transect 2 temperature loggers and pressure transducer

372312120481080 RW-080 0.5 upstream, transect 2 temperature loggers

372312120481081 RW-081 3 upstream, transect 2 none

372312120481071 BW-071 3.5 upstream, transect 2 none

372312120481072 BW-072 5 upstream, transect 2 temperature loggers

372312120481051 BW-051 3.5 downstream, transect 1 none

372312120481052 BW-052 5 downstream, transect 1 temperature loggers

372312120481043 RW-043 0.5 downstream, transect 1 pressure transducer

372312120481044 RW-044 3 downstream, transect 1 temperature loggers and pressure transducer

372312120481034 RW-034 0.5 downstream, transect 1 pressure transducer

372312120481035 RW-035 3 downstream, transect 1 temperature loggers and pressure transducer

372312120481025 RW-025 0.5 downstream, transect 1 none

372312120481026 RW-026 3 downstream, transect 1 temperature loggers

372312120481016 BW-016 3.5 downstream, transect 1 none

372312120481017 BW-017 5 downstream, transect 1 temperature loggers and pressure transducer

1

Additional information in table 1.

Table 8. Monitoring well identification number, depth, location, and type of data collected.

[BW, blank well; ID, identification; RW, river well]
Estimating Seepage Using Heat as a Tracer 33

Flux Estimates from Heat- and Water-Flow Model 

Analyses

One-dimensional modeling of heat and water flow was 

used to interpret temperature and head observations and to 

estimate vertical sw–gw fluxes at wells RW044 and RW035 

in the downstream transect. Two vertical, one-dimensional 

models with 2-cm grid-blocks were calibrated for each of the 

deep monitoring wells at the downstream transect, and each 

well was modeled separately (fig. 25). 

The energy transport and water-flow model, VS2DH, was 

used to fit simulated temperatures to observed temperatures 

and heads. At the beginning of the study, the intention was 

to apply recorded pressure head of the surface water to the 

top boundary and pressure head of the deep monitoring 

wells to the bottom boundary of each of the one-dimensional 

models. However, because of issues with the quality of data 

of the surface-water pressure transducer as discussed in the 

total-head distribution section, a new approach to applying 

pressure-head data to the model was necessary. 

–0.10

–0.05

0

0.05

Mar. 2004

Apr. 2004

May 2004

June 2004

July 2004

Aug. 2004

Sept. 2004

Oct. 2004

Nov. 2004

Dec. 2004

Jan. 2005

Feb. 2005

Mar. 2005

Apr. 2005

May 2005

June 2005

July 2005

Aug. 2005

Sept. 2005

Oct. 2005

0

20

40

60

80

100

120

140

160

–0.10

–0.05

0

0.05

0.10

Mar. 2004

Apr. 2004

May 2004

June 2004

July 2004

Aug. 2004

Sept. 2004

Oct. 2004

DELTA H, IN METERS DELTA H, IN METERS

0

10

20

30

40

50

MEAN DAILY DISCHARGE, IN CUBIC

METERS PER SECOND 

MEAN DAILY DISCHARGE, IN CUBIC

METERS PER SECOND 

Delta H

Discharge (site ID 11272500)

A Delta H = RW044 – RW043

B Delta H = RW035 – RW034

Figure 22. Head differences (delta H) between deep and shallow well pairs. A. Deep pair RW044–RW043. 

B. Shallow pair RW035–RW034. (delta H, water level difference between the deep and shallow monitoring wells. ID, 

identification; no., number; RW, river well.)
34 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

40

100

DAILY MEAN DISCHARGE,

IN CUBIC METERS PER SECOND

DAILY MEAN TEMPERATURE,

IN DEGREES CELSIUS

DAILY MEAN TEMPERATURE,

IN DEGREES CELSIUS

DAILY MEAN TEMPERATURE,

IN DEGREES CELSIUS

11

22

11

22

11

22

Nov. Jan. Mar. May July Sept. Nov. Jan. Mar. May July Sept.

Nov. Jan. Mar. May July Sept. Nov. Jan. Mar. May July Sept.

Nov. Jan. Mar. May July Sept. Nov. Jan. Mar. May July Sept.

Nov. Jan. Mar. May July Sept. Nov. Jan. Mar. May July Sept.

2003–2005

Merced River, near Stevinson (site ID no. 11272500)

RW-044

RW-035

RW-026

River temperature (site 701)

Temperature at 0.5 m (site 045)

Temperature at 1 m (site 046)

Temperature at 2 m (site 047)

River temperature (site 701)

Temperature at 0.5 m (site 036)

Temperature at 1 m (site 037)

Temperature at 2 m (site 038)

River temperature (site 701)

Temperature at 0.5 m (site 027)

Temperature at 1 m (site 028)

Temperature at 2 m (site 029)

Figure 23. Temperature profiles collected at instrumented in-stream monitoring wells at the downstream 

transect (transect 1) during the study period. The line breaks on the graph represent missing data. The three 

digit site number in the figure legend refers to the USGS site identification number with reference to figure 2

and table 1. (ID, identification; m, meter; no., number; RW, river well; USGS, U.S. Geological Survey.)
Estimating Seepage Using Heat as a Tracer 35

18

20

22

24

26

TEMPERATURE, IN DEGREES CELSIUS

June 1, 2004June 2, 2004June 3, 2004June 4, 2004June 5, 2004June 6, 2004June 7, 2004

Temperature at 3.5 m below LS (site 018)

Temperature at 4 m below LS (site 019)

Temperature at 5 m below LS (site 020)

River temperature (site 701)

Figure 24. Diurnal scale of temperature profile for monitoring well BW-017 during June 2004. The three digit site number in the Figure 

legend refers to the USGS site identification number with reference to figure 2 and table 1. (LS, land surface; m, meter; USGS, U.S. 

Geological Survey.) 

18

19

20

21

22

23

18 20 22 24 26 28

HORIZONTAL DISTANCE, IN METERS

ELEVATION, IN METERS

Streambed

Temperature loggers

Screened interval of

monitoring wells

Pressure transducer

1-D model domain

Monitoring well casing

Middle in-stream MW North in-stream MW

Downstream transect

EXPLANATION

Figure 25. Cross-section of downstream transect (transect 1) showing measurement locations and model domain. (D, dimensional; 

MW, monitoring well.)
36 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

The difference in pressure head between the deep and 

shallow wells was assigned to the bottom boundary, and 

a pressure head of 0 was assigned at the sediment–water 

interface (top boundary) for the model. Positive pressure heads 

indicate discharge from the aquifer to the stream. Figure 25

depicts the model domain at 2 m below the streambed, with 

a lower model boundary that corresponds to the deepest 

temperature logger; however, the screened interval of the MW 

is at 3 m below the streambed. As a result, the head difference 

between a deep and shallow well is over a vertical distance of 

2.5 m and does not match the model domain. It was assumed 

that the measured head difference over 2.5 m was linear and 

that K of the materials throughout the model domain was 

constant as a result of the homogenous streambed material. 

Therefore, the head difference over 2.5 m was corrected to a 

head difference over 2 m to match the model domain. 

The temperatures applied to the top and bottom 

boundaries were recorded above the sediment–water interface 

and 2 m below the streambed, respectively. Estimates of 

streambed hydraulic conductivity were input into the model 

until model simulations provided a “best fit” of observed 

temperatures at depth. The observed temperatures used to 

match model simulations were measured were 0.5 and 1.0 

m below the streambed. Figures 26 and 27 depict the results 

of the one-dimensional modeling efforts at the downstream 

transect for in-stream monitoring wells RW-044 and RW-035, 

respectively.

The streambed of the lower Merced River Basin proved 

to be a highly dynamic system, with mobile bar forms 

and substantial bed load transport during periods of low 

streamflow. High streamflow events also included suspended 

load. The model results in figures 26 and 27 depict periods 

where simulated temperatures nearly match observed 

temperatures. Periods of departure have three explanations: 

(1) they may be the result of the streambed characteristics 

changing over time, resulting in varying K values; (2) they 

may be a result of scour near wells that changes the effective 

depth of the temperature loggers and alters the model domain; 

and (3) the hydraulic head gradient that the model calculates 

is over a 2-m domain; however, changes in effective depth of 

pressure transducers that are due to scour near wells may not 

always coincide with the assumed model domain, resulting in 

calculated head gradients that are not representative of actual 

gradients. 

Figure 26 depicts the simulated temperatures and 

modeled flux from March to September 2004 for monitoring 

well RW-044 and may be an exception to the explanations for 

departures from simulated temperatures as explained above. 

The pressure transducer in this monitoring well did not record 

a flow reversal during the April 2004 VAMP release and 

showed significant “noise” after the first data download in 

May 2004. The author of this report believes that this pressure 

transducer was faulty and failed after the second and last 

download in September 2004. The noise in the pressure-head 

data may explain why simulated temperatures were slightly 

higher than the actual temperatures recorded at approximately 

0.5 and 1.0 m below the streambed. 

Figure 27 depicts modeling results for monitoring 

well RW-035. Simulated temperatures match up until the 

dam release in October 2004. A departure from observed 

temperatures occurs during and following the dam release. The 

higher streamflow likely scoured out the fines accumulated 

over the summer prior to the October release, thereby 

increasing the streambed K. The departure of simulated 

temperatures from observed temperatures for this period 

indicates that for the simulated temperatures to continue 

to match the observed temperatures, the streambed K (and 

resultant vertical flux) must be higher than the model input 

value used prior to this period. Figure 28 depicts the results 

of a model run in which the streambed K was increased 

from 1 to 10 m/day for the period of departure (10/18/2004 

to 1/25/2005). The resultant simulated temperatures for the 

departure period provide an improved match-to-observed 

temperatures and substantiate the interpretation for this 

departure. The resultant modeled vertical flux increased from 

0.4 to 4.6 cm/day. 

Although increasing hydraulic conductivity improves 

the simulated temperatures compared with the observed 

temperatures, it is difficult to accept that this factor alone 

explains the departure because it unlikely that vertical flux 

increased an order of magnitude over such a short period of 

time. Instead, a combination of factors may better explain 

the departure. It is likely that changes in effective depth of 

pressure transducers, attributed to scour near wells, resulted in 

instrumentation depth not coinciding with the assumed model 

domain. The result is that the head gradients that the model 

calculates are not representative of actual gradients. This 

explanation coupled with increased streambed K resulting 

from scouring of fines because of higher streamflow may 

provide a more accurate explanation of the departure.

Because of the data gap that occurs between January and 

February 2005 for monitoring well RW-035, and departure 

period following the October 2004 dam release, the model 

was run as three separate modeling periods. Table 9 lists the 

well name, modeling period, thermal conductivity, hydraulic 

conductivity, and average vertical flux input values of 

hydraulic, thermal conductivity, and average vertical flux. 
Estimating Seepage Using Heat as a Tracer 37

0

5

10

15

20

25

30

35

40

45

–20

–15

–10

–5

0

5

10

VERTICAL FLUX, IN CENTIMETERS PER DAY

0

5

10

15

20

25

30

35

A Simulated and observed temperatures at 0.5 m for RW-044

B Simulated and observed temperatures at 1.0 m for RW-044

C Discharge and modeled flux for RW-044

Mar. 2004

Apr. 2004

May 2004

June 2004

July 2004

Aug. 2004

Sept. 2004

Mar. 2004

Apr. 2004

May 2004

June 2004

July 2004

Aug. 2004

Sept. 2004

Mar. 2004

Apr. 2004

May 2004

June 2004

July 2004

Aug. 2004

Sept. 2004

0

5

10

15

20

25

30

35

TEMPERATURE, IN DEGREES CELSIUS TEMPERATURE, IN DEGREES CELSIUS

DAILY MEAN DISCHARGE, 

IN CUBIC METERS PER SECOND

River temperature (site 701)

Observed temperature at 0.5 m (site 045)

Simulated temperature at 0.5 m

River temperature (site 701)

Observed temperature at 1 m (site 046)

Simulated temperature at 1 m

Discharge (site ID no. 11272500)

Modeled vertical flux

Figure 26. Plots of observed and simulated temperatures for monitoring well RW-044. 

A. At 0.5 meters below the sediment–water interface. B. At 1 meter below the sediment–

water interface. C. Resultant modeled vertical flux and stream discharge. The line breaks 

on the graphs represent missing data. The three digit site number in the Figure legend 

refers to the USGS site identification number with reference to figure 2 and table 1. (ID, 

identification; m, meter; no., number; RW, river well; USGS, U.S. Geological Survey.) 
38 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

0

20

40

60

80

100

120

140

160

–20

–15

–10

–5

0

5

VERTICAL FLUX, IN CENTIMETERS PER DAY

discharge (site ID no. 11272500)

modeled vertical flux

A Simulated and observed temperatures at 0.5 m for RW-035

B Simulated and observed temperatures at 1.0 m for RW-035

C Modeled flux and discharge for RW-035

Apr. 2004Apr. 2005

Feb. 2004

June 2004

Aug. 2004

Oct. 2004

Dec. 2004

Feb. 2005

June 2005

Aug. 2005

Oct. 2005

Dec. 2005

Apr. 2004

Apr. 2005

Feb. 2004

June 2004

Aug. 2004

Oct. 2004

Dec. 2004

Feb. 2005

June 2005

Aug. 2005

Oct. 2005

Dec. 2005

Apr. 2004Apr. 2005

Feb. 2004

June 2004

Aug. 2004

Oct. 2004

Dec. 2004

Feb. 2005

June 2005

Aug. 2005

Oct. 2005

Dec. 2005

TEMPERATURE, IN DEGREES CELSIUS TEMPERATURE, IN DEGREES CELSIUS

DAILY MEAN DISCHARGE,

IN CUBIC METERS PER SECOND

River temperature (site 701)

Observed temperature at 0.5 m (site 036)

Simulated temperature at 0.5 m

River temperature (site 701)

Observed temperature at 1 m (site 037)

Simulated temperature at 1 m

Figure 27. Plots of observed and simulated temperatures for monitoring well RW-035. 

A. At 0.5 meters below the sediment–water interface. B. At 1 meter below the sediment–

water interface. C. Modeled vertical flux and stream discharge. The line breaks on 

the graphs represent missing data. The three digit site number in the Figure legend 

refers to the USGS site identification number with reference to figure 2 and table 1. (ID, 

identification; m, meter; no., number; RW, river well; USGS, U.S. Geological Survey.) 
Estimating Seepage Using Heat as a Tracer 39

0

5

10

15

20

25

30

TEMPERATURE, IN DEGREES CELSIUS TEMPERATURE, IN DEGREES CELSIUS

Observed temperature at 0.5 m

Simulated temperature at 0.5 m, K = 1 m/day

Simulated temperature at 0.5 m, K = 10 m/day

0

5

10

15

20

25

30

Observed temperature at 1 m

Simulated temperature at 1 m, K = 1 m/day

Simulated temperature at 1 m, K = 10 m/day

A Simulated and observed temperatures at 0.5 m for RW-035

B Simulated and observed temperatures at 1.0 m for RW-035

Feb. 2004

Apr. 2004

June 2004

Aug. 2004

Oct. 2004

Dec. 2004

Feb. 2005

Apr. 2005

Feb. 2004

Apr. 2004

June 2004

Aug. 2004

Oct. 2004

Dec. 2004

Feb. 2005

Apr. 2005

Monitoring 

well ID 

number

Modeling 

time 

period

Thermal 

conductivity 

(W/m oC)

Hydraulic 

conductivity 

(m/day)

Average 

vertical flux 

(cm/day)

RW-035 3/10/2004–10/18/2004 1.8 1.0 0.4

RW-035 110/18/2004–1/25/2005 1.8 10 4.6

RW-035 2/22/2005–10/2/2005 1.8 2.6 0.5

RW-044 3/10/2004–9/20/2001 1.8 2.6 1.1

1

Departure period depicted in figure 28.

Table 9. Modeling input values of listed parameters for modeling periods listed.

[°C, degrees Celsius; cm, centimeter; ID, identification; m, meter; RW, river well; W, watt]
40 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

Conclusions

Estimates of vertical flux across the sediment–water 

interface were made by direct measurement using seepage 

meters and a heat as tracer method in a 100-m reach of the 

lower Merced River. Results of the temperature modeling 

efforts indicate that the Merced River at the study reach is 

generally a slightly gaining stream with very small head 

differences between surface water and ground water, and has 

flow reversals that can occur during high streamflow events. 

The period of study included a large range of streamflow 

that affected the streambed characteristics and hydraulic 

conductivity of the streambed. The high streamflow events 

associated with storm runoff events and large releases at the 

upstream dam resulted in an increase in hydraulic conductivity 

that probably was due to the scouring of fines accumulated 

during periods of low streamflow. The application of heat as a 

tracer method resulted in average vertical flux estimates across 

the sediment–water interface of 0.4–2.2 cm/day for the study 

period. The range of vertical hydraulic conductivities used in 

heat as a tracer model (VS2DH) was 1–10 m/day at the study 

reach.

The use of seepage meters to directly measure vertical 

flux generally failed in this high-energy system because of 

slow seepage rates and a mobile streambed that scoured or 

buried the seepage meters. Slug tests and grain-size analysis 

were directly compared to characterize the streambed 

hydraulic conductivity. Lateral hydraulic conductivities 

determined using slug tests ranged from 40 to 250 m/day 

at the upstream transect and from 10 to 100 m/day at the 

downstream transect. The locations of screened intervals 

likely explains variability in range of estimates. Variability 

in hydraulic conductivity for the grain-size method ranged 

from 50 to 110 m/day and 20 to 70 m/day for the upstream 

and downstream transects, respectively. The relative percent 

difference between hydraulic conductivity estimates by 

grain size and slug test for wells screened at 0.5 m below the 

sediment–water interface was 0–9 percent at the upstream 

transect and 80–133 percent at the downstream transect. 

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Appendix

[cm, centimeter; ID, identification; mL, milliliter; PC, parameter code]

Sampling Event 1

December 2–4, 2003

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

December 2–3, 2003 December 3–4, 2003

372312120480007 A shower bag 0.01 –0.5

372312120480008 1 medical bag –1.5 –1.1

372312120480009 B shower bag –0.16 0.11

372312120480010 2 medical bag –2.1 –2.2

372312120480011 C shower bag 0.24 0.2

372312120480012 3 medical bag lost stopper 0.5

372312120480001 D shower bag 0.02 0.16

372312120480002 4 medical bag –1.5 –1.7

372312120480003 E shower bag 0.07 0.15

372312120480004 5 medical bag 0.06 1.2

372312120480005 F shower bag –0.48 –0.08

372312120480006 6 medical bag 0.19 –0.48

Sampling Event 2

January 29–31, 2004

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

January 29–30, 2004 January 30–31, 2004

372312120480007 A shower bag 0.05 0.06

372312120480008 1 medical bag 0.19 0.89

372312120480009 B shower bag 0.2 0.24

372312120480010 2 medical bag –0.57 0.13

372312120480011 C shower bag 0.15 0.15

372312120480012 3 medical bag –1.2 –1.9

372312120480001 D shower bag1 0.15 –0.01

372312120480002 4 medical bag1 –0.03 –1.9

372312120480003 E shower bag1 0.13 complete scour of meter

372312120480004 5 medical bag1 –1.7 –2.2

372312120480005 F shower bag1 0.18 –0.43

372312120480006 6 medical bag1 –0.22 –1.9

1

Indicates shower bag used in the first 24-hour measurement period and packaging bag used in the second 24-hour measurement period.

References 45
Sampling Event 3

February 10–12, 2004

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

February 10–11, 2004 February 11–12, 2004

372312120480007 A shower bag 0.2 0.17

372312120480008 1 medical bag 0.83 0.16

372312120480009 B shower bag 0.07 –0.02

372312120480010 2 medical bag –2.1 –2

372312120480011 C shower bag 0.18 0.01

372312120480012 3 medical bag 0.03 –0.79

372312120480001 D shower bag1 –0.03 –0.02

372312120480002 4 medical bag1 –1.4 –2

372312120480003 E shower bag1 0.13 0.11

372312120480004 5 medical bag1 –2 1.3

372312120480005 F shower bag1 –0.04 0.56

372312120480006 6 medical bag1 –0.06 0.2 1

Indicates shower bag used in the first 24-hour measurement period and packaging bag used in the second 24-hour measurement period.

Sampling Event 4

July 19–21, 2004

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

July 19–20, 2004 July 20–21, 2004

372312120480007 A packaging bag 0.43 0.61

372312120480008 1 packaging bag –1.3 0.45

372312120480009 B packaging bag 0.46 –0.1

372312120480010 2 packaging bag –1.6 4.3

372312120480011 C packaging bag 0.38 0.71

372312120480012 3 packaging bag 2.8 4.2

372312120480001 D packaging bag 0.39 –0.23

372312120480002 4 packaging bag –1.7 1.2

372312120480003 E packaging bag 0.11 0.75

372312120480004 5 packaging bag housing unit dislodged 4.2

372312120480005 F packaging bag 0.35 0.58

372312120480006 6 packaging bag 0.79 –0.41

Appendix–Continued.

[cm,centimeter; ID, identification; mL, milliliter; PC, parameter code]

46 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California
References 47

Sampling Event 5

September 20–22, 2004

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

September 20–21, 2004 September 21–22, 2004

372312120480007 A packaging bag 0.31 0.23

372312120480008 1 packaging bag –0.16 –0.11

372312120480009 B packaging bag collection bag disconnected 0.43

372312120480010 2 packaging bag –1.1 –0.63

372312120480011 C packaging bag –0.05 0.52

372312120480012 3 packaging bag –1.1 –0.23

372312120480001 D packaging bag hole developed in collection bag 0.4

372312120480002 4 packaging bag 0.14 0.77

372312120480003 E packaging bag 0.6 –0.11

372312120480004 5 packaging bag –1 –0.55

372312120480005 F packaging bag 0.43 0.03

372312120480006 6 packaging bag –0.9 0.12

Sampling Event 6 

September 22–23, 2004

USGS site 

ID number

Seepage 

meter Bag type

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

Hyporheic flux of water from 

ground water to surface water 

(mL/cm2/day) 

PC 99066

September 21–22, 2004 September 22–23, 2004

372312120480007 A packaging bag 0.23 0.14

372312120480008 1 packaging bag –0.11 0.46

372312120480009 B packaging bag 0.43 0.11

372312120480010 2 packaging bag –0.63 1

372312120480011 C packaging bag 0.52 0.06

372312120480012 3 packaging bag –0.23 –1.2

372312120480001 D packaging bag 0.4 0.12

372312120480002 4 packaging bag 0.77 0.8

372312120480003 E packaging bag –0.11 0.27

372312120480004 5 packaging bag –0.55 1.3

372312120480005 F packaging bag 0.03 –0.15

372312120480006 6 packaging bag 0.12 –0.4

Appendix–Continued.

[cm,centimeter; ID, identification; mL, milliliter; PC, parameter code]
48 Estimating Water Fluxes Across the Sediment–Water Interface in the Lower Merced River, California

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