AN ABSTRACT OF THE THESIS OF
Christopher T. Gregory for the degree of Master of Science in Water Resources
Engineering presented on December 10, 2009.
Title: Temperature and Infiltration Characterization of a Constructed Wetland for
Wastewater Treatment
Abstract approved:
John S. Selker
The City of Woodburn, Oregon’s Wastewater Treatment Plant (WWTP) has been
investigating several natural alternatives for improving effluent quality. Based on its
current National Pollution Discharge Elimination System (NPDES) permit, the
WWTP will require additional reduction of temperature and ammonia levels in the
summer, especially in the critical month of September.
The present research focuses on the performance of a 0.15 ha constructed pilot
wetland during the summer and early fall of 2009. The wetland was intended to
demonstrate the feasibility of using treatment wetlands to lower temperature and
ammonia during an annual operational period (approximately June through October).
Point sensors and a fiber optic distributed temperature sensor (DTS) were used to
assess temperature treatment during the study. Infiltration was monitored to
characterize the hydrogeologic behavior of the site. A wetland water budget was used
to determine system-wide infiltration, and heat pulses applied to a subsurface fiber
optic cable were used to assess infiltrative variability.
The results showed that temperature reduction in the pilot wetland was marginal over
the study period. In the September critical month, significantly more treatment
occurred in the WWTP storage lagoon than in the wetland (about 4°C cooling
compared to 1.2°C in the wetland). Decreasing the hydraulic retention time from 2.5
to 0.5 days in mid-September did not change the average temperature treatment. DTS
data demonstrated that all temperature reduction occurred in the first half of the
wetland. Infiltration was greater than outflow for most of the study, and steadily
decreased through time. The highest and lowest infiltration velocities were within a
factor of 2, and this range also declined between November 2008 and June 2009.
Potential explanations for decreasing infiltration include soil clogging and settling.
The study showed the utility of DTS for assessing the spatial and temporal variability
of infiltration processes.
© Copyright by Christopher T. Gregory
December 10, 2009
All Rights Reserved
Temperature and Infiltration Characterization of a Constructed Wetland for
Wastewater Treatment
by
Christopher T. Gregory
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Presented December 10, 2009
Commencement June 2010
Master of Science thesis of Christopher T. Gregory presented on December 10, 2009.
APPROVED:
Major Professor, representing Water Resources Engineering
Director of the Water Resources Graduate Program
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my thesis to any
reader upon request.
Christopher T. Gregory, Author
ACKNOWLEDGEMENTS
First and foremost, I would like to express my sincere appreciation to
Professor John S. Selker. Thank you, John, for your inspiration in the classroom,
example in the field, and generosity as a friend. I have been blessed to be a part of
your research team.
Thanks to the City of Woodburn Wastewater Treatment Plant staff for their
teamwork and coordination on most of the wetland work. Special acknowledgement
goes to plant supervisor Curtis Stultz, for his helpfulness and reliability over the last
18 months, and utility workers Mike Arellano, Jason Garner, and Ramon Garcia.
Thanks to the greater Woodburn WWTP research team: Jason Smesrud at
CH2M HILL, and the ―Woodburn Warriors‖—Daniel Moreno, Kyle Chambers, and
Ryan Stewart. Your camaraderie made all the difference.
I would also like to thank John Bolte, Roy Haggerty, and Deborah Pence for
serving on my committee. Thanks to Nick Tufillaro and Frank Selker for their
collaboration on various aspects of the data processing. Nick provided good advice
and timely ideas and Frank was instrumental in getting the MATLAB codes up and
running. Marhaba and thanks to colleague Chadi Sayde for his encouragement and
help throughout my time at Oregon State. Thanks to my parents for their unwavering
support. I love you both.
Lastly, I would like to thank my best friend and wife, Katherine, for her
ongoing love and commitment to see me through life’s ups and downs. I am thrilled
about the spending the rest of my life with you.
CONTRIBUTION OF AUTHORS
Kyle Chambers, Ryan Stewart, and Daniel Moreno were extensively involved in the
installations, data collection, and analysis of this research. Kyle Chambers and Ryan
Stewart were very helpful in the review of these manuscripts. John S. Selker
provided expertise, oversight, and organized the funds for these projects.
TABLE OF CONTENTS
Page
1
2
GENERAL INTRODUCTION .......................................................................1
1.1
Background .........................................................................................1
1.2
Relevance of the Research Project ......................................................2
1.3
Scope and Objectives ..........................................................................3
ASSESSMENT OF TEMPERATURE REDUCTION IN A
CONSTRUCTED WETLAND FOR WASTEWATER TREATMENT ........4
2.1
Abstract ...............................................................................................5
2.2
Introduction .........................................................................................5
2.3
2.4
2.2.1
Wetland Temperatures and the Energy Balance ..................6
2.2.2
Distributed Temperature Sensing ......................................10
Materials and Methods ......................................................................11
2.3.1
Site Description ..................................................................11
2.3.2
Instrumentation ..................................................................13
2.3.3
Fiber Optic Installation ......................................................18
2.3.4
Distribution of Vegetation .................................................19
2.3.5
Hydraulic Retention Time ..................................................20
Results ...............................................................................................22
2.4.1
Full Scale Observations .....................................................22
2.4.2
Spatially Detailed Observations .........................................30
2.5
Summary and Conclusions ...............................................................35
2.6
Acknowledgements ...........................................................................36
2.7
References .........................................................................................36
TABLE OF CONTENTS (Continued)
Page
3
INFILTRATION CHARACTERIZATION OF A CONSTRUCTED
WETLAND FOR WASTEWATER TREATMENT ....................................38
3.1
Abstract .............................................................................................39
3.2
Introduction .......................................................................................39
3.3
3.4
4
3.2.1
The Wetland Water Budget and Infiltration ......................40
3.2.2
DTS and the Heat Pulse Method ........................................44
Materials and Methods ......................................................................46
3.3.1
Site Description ..................................................................46
3.3.2
Instrumentation ..................................................................47
3.3.3
Fiber Optic Installation ......................................................48
3.3.4
Components of a Wetland Water Budget ..........................50
3.3.5
Spatially Distributed Infiltration Rates ..............................53
Results ...............................................................................................58
3.4.1
Full Scale Observations .....................................................58
3.4.2
Spatially Detailed Observations .........................................62
3.5
Summary and Conclusions ...............................................................66
3.6
Acknowledgements ...........................................................................67
3.7
References .........................................................................................68
CONCLUSIONS AND RECOMMENDATIONS .......................................70
BIBLIOGRAPHY .....................................................................................................74
APPENDICES ..........................................................................................................78
Appendix A – An External Calibration Procedure for Distributed
Temperature Sensing Data ....................................................79
Appendix B – Temperature Results of Heat-Pulse: Surfaced Plots of
Heated Cable Segments ........................................................87
Appendix C – Pilot Study Wetland Photographs: Installation and
Vegetative Distribution .........................................................91
LIST OF FIGURES
Figure
Page
2.1
Components of the wetland energy balance ...................................................8
2.2
Map view of Woodburn’s WWTP grounds and the pilot wetland
location with digitized features .....................................................................12
2.3
Locations of sensors and fiber optic cable deployment in pilot wetland. .....14
2.4
Difference in calculated hydraulic head from north and south pressure
transducers ....................................................................................................16
2.5
Ice-slush temperature recorded during DTS study with a high-precision
thermometer ..................................................................................................17
2.6
DTS temperature profile showing the ice-bag placement used to locate
the north end of the westernmost transect.....................................................18
2.7
Wetland temperature treatment observed over summer/fall study ...............23
2.8
Effluent temperatures observed during critical period..................................24
2.9
Correlation between outlet daily temperature range and water level,
with outlet flow rate influencing the water level ..........................................26
2.10
Daily maximum temperatures during critical period, collected from
continuous sensors. .......................................................................................28
2.11
A longitudinal profile of the wetland calculated as the average of all
four transects over a 72-hour period .............................................................31
2.12
Temperature variance in the longitudinal profile over 72 hours...................32
2.13
All points along the wetland longitudinal temperature profile .....................33
2.14
Inlet, outlet, and East S. Midzone 10-minute temperatures at the
beginning of the September critical period ...................................................34
2.15
Temperature variance observed over 72 hours in all four transects .............34
3.1
Components of the wetland water budget .....................................................41
LIST OF FIGURES (Continued)
Figure
Page
3.2
Location of sensors and fiber optic cable depths in pilot wetland. ...............50
3.3
Blueprint of pilot wetland .............................................................................51
3.4
Rise in cable temperature, ΔT, observed over heating duration....................55
3.5
Variation in cable heating response across a 20 m segment .........................55
3.6
Components of the wetland water budget as fluxes (cm/d) ..........................59
3.7
Infiltration rate and water depth during the summer/fall study period .........60
3.8
Water levels in two piezometers nearest the wetland and inlet flow rate .....61
3.9
Relative variability of north wetland infiltration based on the thermal
response of heated fiber optic cables ............................................................63
3.10
Relative variability of south wetland infiltration based on the thermal
response of heated fiber optic cables ............................................................64
3.11
Relative variability of north wetland infiltration based on data collected
in June of 2009 using a 1-hour heat pulse with about 15 cm of standing
water ..............................................................................................................65
3.12
Relative variability of north wetland infiltration based on data collected
in June of 2009 using a 1-hour heat pulse with about 15 cm of standing
water ..............................................................................................................65
LIST OF TABLES
Table
Page
2.1
July 2009 weather data for Aurora, Oregon
(source: wunderground.com) ........................................................................23
2.2
Effluent temperature treatment observed during critical period ...................25
2.3
Hydraulic retention time (HRT) calculation components and values for
critical period ................................................................................................27
2.4
Daily maximum temperatures for DMR, inlet, and outlet locations.............29
LIST OF APPENDIX FIGURES
Figure
Page
A.1
An uncalibrated fiber optic cable temperature profile with ice bath
sections on both ends ....................................................................................82
A.2
Ice bath temperature collected in the field with a high-precision
thermometer ..................................................................................................82
A.3
Offset correction (red) applied to temperature data ......................................83
A.4
Attenuation correction (black) applied to temperature data .........................83
A.5
Temperature data for a cable with an ice bath section (at 120 m) and
a water bath section (at 240 m) .....................................................................84
A.6
Water bath temperature collected in the field with a high-precision
thermometer ..................................................................................................84
A.7
Gain correction (green) applied to temperature data ....................................85
A.8
Calibrated cable (green) with offset, attenuation, and gain corrections .......85
B.1
Surfaced plot of DTS heat pulse data showing ―NEW‖ cable segment .......88
B.2
Variability in heating of ―NEW‖ segment shown across cable length .........88
B.3
Variability in heating and cooling of ―NEW‖ segment ................................89
B.4
Variability in heating of ―NWE‖ segment ....................................................89
B.5
Variability in heating of ―SEW‖ segment .....................................................90
B.6
Variability in heating of ―NWW‖ segment ...................................................90
C.1
Elevated view of the pilot wetland from the south end looking north ..........92
C.2
Custom designed plow for installing fiber optic cable in wetland soil
at various depths ...........................................................................................92
C.3
The plow path of a longitudinal transect after cable installation (left)
and an up-close look at the plow path seam before manual
compaction (right) .........................................................................................93
LIST OF APPENDIX FIGURES (Continued)
Figure
Page
C.4
Two longitudinal transects plowed on the eastern half of the wetland .........93
C.5
Fully-vegetated northern half of the east side of the wetland with
middle deep zone labeled ..............................................................................94
C.6
Hydrocotyle in the western middle area .......................................................94
C.7
Hydrocotyle partially covering the south deep zone.....................................95
C.8
Eastern (left) and western (right) fully-vegetated northern zones ................95
C.9
Eastern half of the wetland looking south from middle deep zone with
digitized locations of the fiber optic transects ..............................................96
C.10
Pilot wetland conditions during November 2008 heat pulse ........................96
C.11
Algae growth in the west middle zone in early July 2009 ............................97
C.12
Algae growth in the wetland in late July 2009 .............................................97
Dedicated to the Creator of this world and all its science.
Temperature and Infiltration Characterization of a Constructed Wetland for
Wastewater Treatment
1
1.1
GENERAL INTRODUCTION
Background
The City of Woodburn, Oregon’s Wastewater Treatment Plant (WWTP) is currently
investigating new ways to reduce the temperature and ammonia levels of its effluent
in order to meet waste discharge limitations introduced in its most recent National
Pollutant Discharge Elimination System (NPDES) permit. With these limitations in
mind, and projections of even greater wastewater allocations in the future, the City
has contracted environmental engineering consultant CH2M HILL to oversee the
research, design and construction of future WWTP operations.
As a preliminary step, CH2M HILL implemented three pilot-scaled studies at the
WWTP facility, intended to remediate the wastewater in a variety of ways. These
pilot studies include a 0.15-hectare treatment wetland, a poplar tree irrigation area,
and a rock bed filtration system (Healy and Madison, 2006). Based on the results of
these studies, CH2M HILL will advise the City in regards to future operational
components of the WWTP.
In the spring of 2008, in order to assist them in their research of the pilot studies,
CH2M HILL partnered with John Selker’s group at Oregon State University. Under
the guidance of professional engineers at CH2M HILL, Selker’s group has been
responsible for most of the scientific monitoring, data collection and maintenance of
the pilot systems. The present research involves an in-depth look at the operation and
effectiveness of the 0.15-hectare treatment wetland pilot study. Specifically, the
wetland was assessed for its temperature treatment and infiltration performance
during the summer of 2009, with additional attention given to the WWTP’s
anticipated ―critical period‖ for temperature, occurring in the first half of September.
2
1.2
Relevance of the Research Project
In order for the City of Woodburn to make informed decisions regarding how to
proceed with future WWTP operations, it is critical that the performance of the pilot
wetland has been well documented and understood. Conclusions made from this
study will not only affect CH2M HILL’s ability to accurately scale-up future wetland
designs, but will also affect the WWTP’s ability to effectively lower effluent
temperatures in compliance with their NPDES permit.
In addition, the use of distributed temperature sensing (DTS) technology in a wetland
setting is a groundbreaking application. Lowry et al. (2007) examined variability of
groundwater discharges into a wetland stream using a DTS instrument, but as far as
the author is aware, the DTS application employed here—to determine spatially
distributed infiltration rates and observe temperature treatment in a wetland—has
never before been attempted. Results from this research are hoped to encourage
additional applications of DTS technology in environmental systems.
1.3
Scope and Objectives
The objectives of this research were to characterize the temperature treatment and
infiltration performance of the Woodburn WWTP pilot wetland. These objectives
were to be achieved on two levels: through broad and detailed observations. Broad
observations were conducted using customary instrumentations and procedures, and
were intended to provide basic information about wetland performance. Once this
level of understanding was established, detailed observations with the DTS
instrument was intended to provide insights into the inner workings of the wetland
that were not otherwise available.
3
The body of this work has been divided into two parts, representing the two
objectives. First, temperature treatment of wetland effluent are reviewed based on
point measurements taken at the inlet, outlet and interior of the wetland,
complemented with four longitudinal temperature profiles obtained with a fiber optic
DTS instrument. Second, wetland infiltration rates are presented based on inferred
values obtained from a wetland water budget, in addition to observed variability
determined with a DTS heat-pulse method applied to subsurface fiber optic cables.
The last chapter summarizes conclusions and provides recommendations based on the
research findings.
4
2
ASSESSMENT OF TEMPERATURE REDUCTION IN A
CONSTRUCTED WETLAND FOR WASTEWATER TREATMENT
Chris Gregory, John S. Selker, Kyle Chambers
Department of Biological and Ecological Engineering
Oregon State University, Corvallis, OR 97331
For Submission to Environmental Science and Technology
5
2.1
Abstract
Thermal pollution can be successfully remediated through the use of natural systems.
This study presents the monitoring results from a 0.15 ha surface flow treatment
wetland during the summer and early fall of 2009. Point sensors and a distributed
fiber optic cable were used as complementary methods for assessing wetland
temperature treatment. Wetland inflows were found to already have been pre-treated
in a storage lagoon, which cooled the wastewater effluent by about 4°C in September.
Additional temperature treatment in the wetland was marginal over the study period.
Reducing the hydraulic retention time from 2.5 to 0.5 days in September showed no
decrease in average wetland treatment, indicating that retention time was above
needed. An intensive 3-day fiber optic study at the beginning of September showed
all temperature reduction occurring in the first half (25 m) of the wetland. Fiber optic
sensing also revealed the diel heating and cooling patterns of nearly the entire
wetland surface water.
2.2
Introduction
As new National Pollutant Discharge Elimination System (NPDES) permits are
issued to burgeoning cities around the county, many Wastewater Treatment Plants
(WWTPs) are beginning to incorporate natural systems into their strategy for
improving wastewater quality. Not only do natural systems provide valuable
chemical and physical treatment, aesthetical value, and often ecological habitat,
natural systems can be significantly cheaper to operate and maintain than other
alternatives (Kadlec, 2008).
In 2004, the City of Woodburn was issued a new NPDES permit with stricter
limitations for discharge from its WWTP into the Pudding River (Healy and Madison,
2006). Based on the permit limitations and projected city growth over the next
decade, the WWTP identified ammonia levels and water temperature as needing
additional remediation to meet NPDES limits in the summer and early fall. The
6
City’s course of action was to begin researching natural alternatives to incorporate
into the final stage of their WWTP operations.
One such alternative was the use of treatment wetlands at the WWTP site. Treatment
wetlands have been shown to be effective in treating wastewater for decades in a wide
range of climates (Wittgren and Maehlum, 1997; Kadlec, 2008). The primary
purpose of the wetlands would be to reduce the temperature of effluent leaving the
plant before reaching the Pudding River, either by surface flow or hyporheic
passageways. As supplemental treatment, the wetlands would provide additional
reduction in ammonia concentrations.
The City of Woodburn commenced its wetlands research by the construction of a 0.15
ha pilot wetland in 2005. The wetland was designed to demonstrate, on a small scale,
the feasibility of using wetlands as an alternative treatment method for meeting
NPDES temperature and ammonia limits. If monitoring of the pilot wetland showed
favorable results in the initial period of observation, the City would consider
incorporating wetlands of increased size in several phases.
The objective of this study was to assess the pilot wetland efficacy for reducing
wastewater temperature. Temperature monitoring was approached using point
measurements as well as high-resolution, fiber optic networks with a distributed
temperature sensor (DTS). Based on the findings of this research, recommendations
to the supervisory engineering firm (CH2M HILL) were made regarding the use of
treatment wetlands for future temperature remediation at the WWTP site.
2.2.1
Wetland Temperatures and the Energy Balance
In many treatment wetland systems, the temperature of incoming and outgoing
effluent is of great importance (Kadlec and Reddy, 2001; Kadlec and Wallace, 2008).
One reason for this is that water temperature in wetlands has been shown to strongly
influence the rate of microbial processes leading to water quality treatment, such as
7
ammonia nitrogen processing (Kadlec and Wallace, 2008; Picard et al., 2005; Werker
et al., 2002; Faulwetter et al., 2009). This is important for wetland designers trying to
both calculate accurate rates of treatment as well as optimize their systems for
removal. Wetland systems in very hot or cold climates can be concerned about
evaporative losses where water is in short supply (Kadlec, 2006) or freezing of the
wetland at various times of the year. Temperature may be an important water quality
parameter in some situations, such as Woodburn’s WWTP, where warm discharges
into nearby rivers detrimentally affect salmon health and spawning. To understand
the main processes governing water temperatures in wetlands, the wetland energy
balance should first be considered.
The wetland energy balance can be simplified to energy inputs and outputs within the
wetland system (Kadlec and Wallace, 2008; Kadlec, 2009). Energy inputs to the
wetland include solar radiation, convective heat transfer from the air, vertical and
lateral ground heat transfer, and thermal energy from wetland inflows. Energy
outputs from the wetland include solar back radiation, evapotranspiration (the
combination of evaporation and transpiration, or ET), convective heat transfer from
the air, vertical and lateral ground heat transfer, and energy exiting in wetland
outflows. Additionally, the change in energy storage, which is particular to the type
of treatment wetland, its porous media, and vegetation, is needed to obtain a closed
energy budget (see Figure 2.1).
A balanced energy system, where no change in storage is occuring, can be written as
Energy Inputs = Energy Outputs
or
RN + Ha + Uwi = λmρET + Uwo + G + CL
where RN = net radiation including solar, atmospheric, and back radiation, MJ/m2·d;
Ha = convective transfer from air, MJ/m2·d; Uwi = energy entering with the water,
MJ/m2·d; λm = latent heat of vaporization of water, MJ/kg (2.453 MJ/kg at 20°C);
ρ = density of water, kg/m3; ET = water lost to evapotranspiration, m/d; Uwo = energy
8
2
2
leaving with water MJ/m ·d; G = vertical conductivity loss to ground, MJ/m ·d; CL =
lateral heat loss to ground.
Figure 2.1 Components of the wetland energy balance. (adapted from Kadlec and
Wallace, 2008)
In wetlands that operate during the summer and fall, like at the Woodburn WWTP,
the primary energy input is solar radiation (Kadlec and Wallace, 2008). Solar
radiation varies daily and annually, and is often available locally from national
climatic weather stations such as the NCDC. A fraction of this solar radiation is
reflected from the wetland surface (referred to as the albedo, α) and is based on
characteristics of the vegetation and amount of open water areas. In addition, net
outgoing long wave radiation propagates back into the atmosphere from the wetland
surface (for equations used to calculate these terms see Kadlec and Wallace, 2008).
9
Conductive losses and gains are typically small enough to be considered negligible
except in the winter (Kadlec and Wallace, 2008). The primary energy components
that respond to solar radiation inputs are ET and air convection. Convection can
either add or take away energy from the wetland while ET only removes energy from
the system. In the case of water cooling, evaporation dissipates energy from the
water surface, thereby reducing the water temperature, while transpiration dissipates
from the vegetation and cools plant surfaces rather than water temperature.
In wetlands that are above freezing, the surface water temperature is most strongly
related to air temperature (Kadlec and Wallce, 2008). This relationship largely
depends on the relative humidity, which correlates with the rate of energy loss to ET.
At low relative humidity, the partial pressure difference at the air-water interface
allows additional energy in the water to be released by evaporation, thereby cooling
the water. At high relative humidity, the partial pressure in the air decreases. This
results in less evaporation until the water temperature heats up to the point at which
the partial pressure of the water is high enough to transfer the same mass of water
through evaporation. The dew point (100% relative humidity) reflects the
temperature and humidity conditions at which the air and water partial pressures are
in equilibrium, and no evaporation occurs. When relative humidity is around 50%,
such as often observed in summer, the water temperature is usually driven by
atmospheric conditions toward the ambient air temperature (Kadlec and Wallace,
2008).
An additional consideration in the treatment of surface water temperatures is the
duration of time that the water resides in the wetland, called the hydraulic retention
time (HRT). As water enters the wetland at higher or lower temperatures than the
wetland system, energy absorbed or lost by the water will be change until it gradually
reaches a balanced temperature. Borrowing terms used by Kadlec and Wallace
(2008), the initial change in water temperature occurs in the accommodation zone of
the wetland; once it has reached a balanced state with all other energy components
10
(where energy absorbed and lost are equal) the water is at the balance temperature.
After reaching the balance temperature of the wetland, the water will no longer
continue to change temperature with increased retention times.
Data compiled by Kadlec and Wallace (2008) show that the HRT required to
overcome the accommodation zone and achieve a balance temperature is on the order
of one to three days. This depends on several factors including the incoming water
temperature, water depth, and climatic conditions (Kadlec and Wallace, 2008).
Where incoming water is considerably warmer than the wetland water, relative
humidity is high, and the ambient air temperature is unusually warm, the HRT
necessary to reach balance temperatures is longer.
2.2.2
Distributed Temperature Sensing
Distributed Temperature Sensor (DTS) systems that acquire fiber-optic temperature
measurements were first developed two decades ago (see Dakin et al., 1985;
Kurashima et al., 1990). Although more commonly used in civil infrastructure
applications (Selker et al., 2006a) recently scientists have taken interest in DTS
systems for their potential to capture extraordinary detail in environmental systems
(e.g., Selker et al., 2006a, 2006b; Tyler et al., 2008; Westhoff et al., 2007; Freifeld et
al., 2008).
DTS uses optical fibers, commonly utilized in telecommunication cables, as
distributed sensors. The DTS instrument sends light pulses through the fibers and a
portion of the light encounters molecules in the silica and is scattered. A smaller
fraction of this scattered light returns back up the fiber in the direction of the light
source and is recorded by an optical sensor in the DTS. Based on the arrival time of
the photons, the DTS is able to use the speed of light in the fiber to calculate the exact
distances from the DTS that the photons were scattered. Ultimately, the DTS uses
both arrival-time data and properties of the returning photons to calculate
temperatures along the entire stretch of fiber, with spatial resolution as small as 0.25
11
m and temperature resolution approaching 0.01 °C, depending on the instrument and
configuration (Selker et al., 2006a).
A number of different techniques are employed by DTS systems to obtain
temperature information from returning photons. Raman-based systems, such as
those used in this research, utilize the Raman scattering principle that occurs as light
passes through the silica fiber. According to this principle, not all light is scattered
elastically—meaning, at the same frequency as the incident light. A very small
percentage is scattered inelastically—at a different frequency than the incident
light—due to an excitation in the encountered molecules. This frequency-shifted
backscatter occurs at both lower and higher frequencies than the incident light. While
the lower frequency, referred to as Stokes backscatter, is largely independent of
temperature, the higher frequency, known as Anti-Stokes backscatter, is temperature
dependent. Using the ratio of Anti-Stokes to Stokes intensities, the temperature of the
fiber at the location of scatter can be accurately calculated (see Tyler et al., 2009 for a
more complete discussion).
The present research used a Sensornet Oryx DTS. Data was continuously collected
on the Oryx DTS using 10 minute integration times with 1 m spatial resolution.
Calibration of the DTS system was a critical component of data collection. Details
about the calibration procedure will be addressed in the following chapter.
2.3
Materials and Methods
2.3.1
Site Description
The pilot wetland was located in the floodplain of the Pudding River near the City of
Woodburn, Oregon’s WWTP (Lat. 45 8’ 70‖ N, Long. 122 47’ 50‖ W, see Figure
2.2). The climate was maritime north temperate, with rainy winter and dry summer
seasons. The wetland was approximately 0.15 hectares, with outer-berm length
dimensions of about 27 by 56 m. Soil classification in the floodplain was Wapato
12
series silty clay loam. Potential for hyporheic exchange with the nearby river was
substantial during irrigation season, as underlying the local floodplain soil was a
shallow groundwater aquifer composed of silt, sand and gravel.
Pilot Wetland
N
P2
P3
0
200m
©
Google
Figure 2.2 Map view of Woodburn’s WWTP grounds and the pilot wetland location
with digitized features. The plant’s storage lagoon is shown (under the ―City of
Woodburn WWTP‖ label) as well as two nearby piezometers used in the infiltration
study—P2 and P3. The northern boundary of the floodplain is cutting across the
photo from northeast to southwest.
The hydraulic regime of the wetland was surface-flow with considerable infiltration
that operated with a 2-day HRT. In order to avoid mixing with the river in the
floodplain, the wetland was only operated during the summer and fall seasons, when
river flow was substantially reduced. Within the wetland were 3 lateral deep
zones—at the north end, midpoint, and south end—that were designed to mix the
13
passing effluent (see Figure 2.3). Additionally, a longitudinal berm running down the
center of the wetland divided the wetland into eastern and western halves.
Water was supplied to the wetland from an elevated storage lagoon located near the
main WWTP facility. Flow into the wetland was gravity-fed through 6‖ PVC piping
and controlled by a ball valve located along the inlet pipe. Typically, the flow rate
was maintained around 60 gpm. Flow leaving the wetland varied depending on the
rate of flow coming in and the operational water depth, which could be controlled via
drainage plates on the outlet side. Upon exiting the wetland, flow was transported
downhill through a network of irrigation pipes to a drainage basin area.
Wetland vegetation consisted primarily of cattails (Typha latifolia) and reed canary
grass (Phalaris arundinacea) emergent in the shallow zones. Shallow and deep water
zones contained Hydrocotyle ssp., with algae and duckweed periodically filling in
open water areas. On the middle and perimeter berms, young willow trees (Salix spp.)
created a vegetative canopy approximately two feet over the wetland water (see
Appendix Figures C.1 and C.9). The distribution of vegetation density was
heterogeneous within the wetland, with the densest stands of vegetation found in the
wetland’s northern half.
2.3.2
Instrumentation
Six Onset HOBO temperature loggers were installed at key points around the
wetland. The first logger was placed at the inlet location within a movable-plate flow
regulator that provided hydraulic head control for the wetland’s northern end. The
logger remained submerged for the duration of the study and recorded the
temperature of inflowing water. A second logger was placed within inches of the
outlet uptake pipe in the south end deep zone, and recorded water temperatures of
flow leaving the wetland. Four other temperature loggers were placed around the
middle deep zone in order to observe temperature treatment in the first half of the
wetland, as well as the effect of density-driven water mixing achieved in the middle
14
deep zone (see Figure 2.3). All Onset loggers were synchronized and recorded
continuous, 10-minute averages.
Flow Direction
Figure 2.3 Locations of sensors and fiber optic cable deployment in pilot wetland.
U.S. customary units are used for length dimensions, corresponding to wetland
blueprints.
The temperature loggers were calibrated in coolers across a broad range of
temperatures. First, they were suspended in a well mixed bath of warm water and
allowed sufficient time to equilibrate with the water, while a high-precision
15
®
thermometer (Control Company Traceable 4000; accurate to ± 0.05°C, 0.001°
resolution) was used to record the temperature of the water bath. Second, the above
procedure was repeated after replacing the warm water with an ice-slush mixture.
Based on the readings of the temperature loggers in comparison to the high resolution
thermometer, the data downloaded from the loggers was then adjusted by a fixed
temperature offset for each logger, calculated as the average error in each logger for
the warm and cold baths.
Two Onset HOBO® U-20 submersible water level loggers were placed in shallowdepth piezometers located in the north and south ends of the wetland. The
piezometers that housed the water level loggers were three-foot, steel well screens
that were manually driven halfway down (1.5 feet) in the deep zones of the north and
south ends. The U-20 loggers were synchronized, and recorded absolute pressures
averages over 10-minute intervals.
Subsequent to collection, data from the U-20s were analyzed for consistency and
reliability. While the two loggers produced near identical results, subtle variability in
the north end U-20 due to accumulation of sediment in the piezometer base made
incorporating this data undesirable (see Figure 2.4) and data from the south U-20
alone was used. In order to calculate water level from the logger’s pressure readings,
atmospheric pressure obtained from the NCDC Aurora State Airport station (call sign
UAO 3S2) was first subtracted from the U-20 pressure values. The remaining
relative pressure was then converted to a hydraulic head using the density of water
and the acceleration of gravity. Hydraulic head was then adjusted by data from a
water depth survey performed in the shallow zones to correspond to water level (or
depth of water in the shallow zones).
16
Difference in North and South Pressure Transducers
Difference in hydraulic head (cm)
3.0
2.0
Data collected & replaced on
about 2 cm of sediment
accumulation in N. piezometer
outlet cleared , increasing
S. outflow
1.0
0.0
-1.0
-2.0
7/16/09
8/5/09
8/25/09
9/14/09
10/4/09
Figure 2.4 Difference in calculated hydraulic head from north and south pressure
transducers. Sediment accumulation in the north piezometer led to an error of about 2
cm when this pressure transducer was removed for data collection and replaced in
early September.
Two Signet 2552 Metal Magmeter flow sensors (Schaffhausen, Switzerland) were
installed in the wetland pipe irrigation system to monitor flow entering and leaving
the wetland. The first flow sensor, located at the inlet control pipe, recorded the flow
entering the wetland from the treatment plant’s storage lagoon. The second flow
sensor was placed at the wetland’s outlet pipe and recorded flow leaving the wetland
via surface flow. Campbell Scientific CR200-series dataloggers used these sensors to
record 5-minute flow averages.
The flow sensors were calibrating using sensor-tip insertion depths based on the
product manual specification for 2-in PVC pipes (10% of pipe inner diameter). To
cross-check instrument readings, a calibrated 5-gallon bucket was used to catch lowflow through the pipes and the volumetric additions were timed with a stopwatch.
17
A Sensornet Oryx DTS system was used in the fiber optic temperature study. Data
was collected on the Oryx using 10-minute integrations with 1 m spatial resolution.
The study lasted over 4 days between 8/29 and 9/2/09, and captured detailed
temperature data for the beginning of the WWTP’s critical temperature compliance
period (9/1-9/15).
Calibration of the DTS data was performed within the Oryx system configuration,
with user-specified fiber conditions validated by field observations. Approximately
10 m of cable from both ends of the cable deployment were wound in coils and
placed together in the same ice-slush mixture. The ice-slush mixture was housed in a
5-day cooler, and carefully maintained at 0° C for the duration of the study (see
Figures 2.5 and 2.6). Using calibration options within the Oryx DTS software, the
longer of the two coils (the far end coil) was given a specified value of 0° to correct
for any offset in the temperature data. Additionally, both coils were specified to have
the same temperature, thus correcting for attenuation in the fiber. These
specifications were incorporated into the DTS data processing and ensured both
consistent and accurate results.
Figure 2.5 Ice-slush temperature recorded during DTS study with a high-precision
thermometer. (Temp. = 0.009°C)
18
On the first day of the study, ice bags were placed at the beginning, midpoint (middle
deep zone) and end of each longitudinal transect. The data were collected using 1minute integrations over a two hour period. Subsequently, the data were used in postanalysis to locate the beginning and end points of each transect, and align them with
the other transects for averaging (see Figure 2.6).
30
Temperature (C)
25
20
15
10
Ice bag placement
5
Ice-slush bath
0
-5
0
50
100
150
200
250
300
Distance from DTS (m)
Figure 2.6 DTS temperature profile showing the ice-bag placement used to locate
the north end of the westernmost transect. The temperature of the ice-slush bath is
shown at the beginning and end of the temperature profile around 0°C.
2.3.3
Fiber Optic Installation
Nearly 300 meters of fiber optic cable was draped and secured along the soil surface
of the wetland. The cable deployment began with approximately 10 m of coiled cable
outside the wetland’s eastern berm, entered through the southern deep zone, and then
made four longitudinal transects of the wetland before exiting through the south end
(see Figure 2.3). Metal stakes with cable hooks were used to loosely secure the cable
in place at each turn in the deep zones. The density of the cable was greater than the
19
effluent and therefore sank to the top of the wetland soil surface. In the north, south
and middle deep zones, the cable sank to a greater depth, and therefore observed
different temperatures and mixing processes than in the shallow zones.
After exiting through the south end of the wetland, the cable returned to the starting
location. The last 10 m of cable were wound into a coil and placed into a cooler with
the first 10 m coil. As described in the previous section, having the beginning and
terminating cable ends together at the same temperature enabled accurate userspecified calibrations in the DTS configuration software.
2.3.4
Distribution of Vegetation
Vegetation within the wetland was characterized by a patchy distribution of dense
vegetative stands. Along with different stages of the growing season reflecting
different quantities of total vegetation, periodic emergence of algae and duckweed, as
well as operational changes to the wetland—such as the addition or relocation of
large hydrocotyle mats—led to ever-changing vegetative conditions.
However, several characteristics of the wetland vegetation that remained more or less
the same throughout the duration of the study. On both the east and west sides, the
northern half of the wetland was consistently more vegetated than the southern half,
with dense, continuous stands of cattail located from the northern deep zone to within
three meters of the middle deep zone (see Appendix Figure C.5). South of the middle
deep zone, the east and west sides both had large open areas with very few cattails.
An exception to this was a strip of cattails that bordered the eastern berm and ran
nearly the full length of the wetland (see Appendix Figure C.9). Towards the
southern end of the wetland, about 2-7 meters of cattails were located just north of the
southern deep zone on both east and west sides.
In addition, the young willow trees located along the middle and perimeter berms
were a continual source of shade for the effluent. The base of the willows were
20
spaced approximately two feet apart, creating a very dense upper canopy. During
early morning and late evening hours, the willows were capable of shading nearly the
entire surface of the wetland (see Appendix Figure C.1).
However, the distribution of Hydrocotyle spp., a floating plant and perhaps the third
most significant shade cover in the wetland, varied greatly throughout the study. In
early and late July, numerous truckloads of Hydrocotyle spp. were added to the open
water areas in the middle of the wetland. After establishing in these areas during in
August, several large Hydrocotyle spp. mats were relocated from the middle of the
wetland to the northern half to fill in the remaining gaps of the canopy. During the
DTS data collection, which lasted from 8/29 to 9/2, Hydrocotyle spp. was present in
the western middle area, the north and south deep zones, and filled in open areas of
the northern half of the wetland (see Appendix Figures C.6, C.7, and C.8).
The presence of algae and duckweed varied greatly throughout the study. In July,
duckweed cover was limited to the northern deep zone and algal growth blossomed in
middle open areas (see Appendix Figures C.11 and C.12). By the middle of August,
the alga was no longer present and duckweed had spread across the full wetland area.
During the DTS study, duckweed was the primary cover for open water areas and
algae was not observed (see Appendix Figure C.9).
2.3.5
Hydraulic Retention Time
Hydraulic retention time (HRT) was calculated using an Excel spreadsheet created by
Jason Smesrud (P.E., CH2M HILL). The spreadsheet determined the volume of
water in the wetland as a function of water depth, using internal wetland geometries
that included deep zones, berms, and shallow areas. HRT was then approximated by
dividing the total water volume by the average of the inlet and outlet flow rates, and
converting this time to days.
21
HRT was approximated for the northern and southern halves of the wetland in order
to better understand the system. To do this, the decrease in flow from the inlet to the
outlet was assumed to be linear (due to uniform losses across the wetland). Based on
this assumption, the flow rate occurring midway through the wetland was
approximated as the inlet and outlet flow average, and the average flow in the
northern and southern halves were approximated as the averages between inlet and
midpoint, and outlet and midpoint, respectively. Taking the northern and southern
flow averages, the HRT for both halves was then calculated as the northern and
southern water volumes divided by their respective flow averages. Using this method
the HRT in the southern half was shown to be about twice as long as the HRT in the
northern half under normal operating conditions with a total 2 day HRT.
While the above methods were approximate, HRT can also be calculated exactly with
an analytical solution in terms of inflow, I, outflow, O, and water depth, H. With
wetland width, W, and length, L, already known, percolation, P, can be assumed as
–
Eq. 2.1
and assuming a linear decrease through the wetland, flow can be written as
Eq. 2.2
where Q(x) is flow as a function of distance, and x is distance from the inlet location.
Velocity, v, can then be solved by
Eq. 2.3
and the differential of time can be written as
Eq. 2.4
Using a change of variables,
Eq. 2.5
where the derivative of both sides is
22
Eq. 2.6
Rearranging for dx gives
Eq. 2.7
The right side of Eq. 2.7 can now be substituted into Eq. 2.4 to give
Eq. 2.8
which can be integrated to get
Eq. 2.9
Finally, retention time, T, can be calculated as
=
2.4
Results
2.4.1
Full Scale Observations
Eq. 2.10
Inlet and outlet temperatures recorded by calibrated loggers showed marginal wetland
temperature treatment over the duration of the study (see Figure 2.7). For most of
July, effluent temperatures showed warming through the wetland of up to 2.5° C,
corresponding to above average air temperatures (see Table 2.1) and less vegetation
than observed later in the summer. Beginning in August, wetland outlet temperatures
decreased to below inlet temperatures and for the most part maintained that pattern
for the rest of the study.
23
Figure 2.8
Figure 2.7 Wetland temperature treatment observed over summer/fall study.
Table 2.1 July 2009 weather data for Aurora, Oregon (source: wunderground.com)
Aurora, Oregon Weather
Date
Avg. High
(°C)
7/15/09
7/16/09
7/17/09
7/18/09
7/19/09
7/20/09
7/21/09
7/22/09
7/23/09
7/24/09
7/25/09
7/26/09
7/27/09
7/28/09
7/29/09
7/30/09
7/31/09
26
27
27
27
27
27
27
27
28
28
28
28
28
28
27
27
27
Obs. High
(°C)
32
34
34
32
29
35
32
29
25
30
34
35
40
41
42
34
36
Avg. Difference (°C)
Difference
(°C)
=
+6
+8
+8
+5
+2
+8
+5
+2
-3
+2
+6
+7
+ 12
+ 13
+ 15
+7
+8
+6.5
24
During the critical month of September, when temperature reduction will be essential
for meeting NPDES permit limits, an average effluent treatment of -1.1° C was
observed (see Figure 2.8 and Table 2.2). From 9/1 through 9/19, outlet temperatures
were consistently lower than inlet temperatures, and the outlet daily range of
temperatures was comparable—and often smaller—than that of the inlet. After 9/19
until 10/1, outlet temperatures continued to be less than inlet temperatures on average,
but the daily range of temperatures increased greatly, resulting in higher outlet
maximum temperatures than inlet maximums on several days.
2-Day Avg. Treatment
Figure 2.8 Effluent temperatures observed during critical period.
25
Table 2.2 Effluent temperature treatment observed during critical period.
Pilot Wetland Treatment
Date
Inlet Avg. Temp.
(°C)
9/1/09
9/2/09
9/3/09
9/4/09
9/5/09
9/6/09
9/7/09
9/8/09
9/9/09
9/10/09
9/11/09
9/12/09
9/13/09
9/14/09
9/15/09
9/16/09
9/17/09
9/18/09
9/19/09
9/20/09
9/21/09
9/22/09
9/23/09
9/24/09
9/25/09
9/26/09
9/27/09
9/28/09
9/29/09
9/30/09
18.79
19.06
18.88
18.74
18.37
18.28
17.95
17.56
17.58
18.05
18.35
18.47
18.51
18.53
18.48
18.52
18.41
17.96
17.64
16.97
16.82
16.77
16.88
16.96
17.07
17.10
16.81
16.44
15.77
15.32
Outlet Avg. Temp.
(°C)
18.45
18.08
18.36
17.37
17.49
16.97
16.44
15.54
15.69
16.71
16.97
18.11
18.47
17.63
17.58
17.62
17.26
15.93
16.32
15.57
15.83
16.22
16.26
15.89
15.90
15.55
15.30
14.53
14.25
13.81
Average Treatment
Difference
(°C)
-0.34
-0.98
-0.53
-1.37
-0.88
-1.31
-1.50
-2.02
-1.89
-1.34
-1.38
-0.36
-0.03
-0.90
-0.90
-0.90
-1.15
-2.02
-1.32
-1.40
-0.98
-0.55
-0.62
-1.07
-1.17
-1.55
-1.52
-1.90
-1.52
-1.51
= -1.2
26
The increase of daily temperature range in the outlet, occurring around 9/20,
coincided with flow changes resulting from the clearance of a blockage in the outflow
of the wetland. Following a period of increased water depth and decreased outflow
due to the blockage, a significant increase in outflow began on 9/19, re-equilibrated
with wetland hydraulic head around 9/22, and was maintained through 10/1 (see
Figure 2.9). By increasing the outflow, the water depth within the wetland was
decreased. The reduced water level greatly impacted the daily range of temperatures
as similar diel energy inputs were applied to substantially smaller volumes of wetland
water.
Water Depth
Flow Out
Figure 2.9 Correlation between outlet daily temperature range and water level, with
outlet flow rate influencing the water level.
Higher outlet flow rates and lower water levels decreased the hydraulic retention time
(HRT) of the wetland effluent. The HRT values were calculated for each day in
September are shown in Table 2.3. Between 9/1 and 9/19, the average HRT was 2.5
days with a standard deviation of 0.7 days. After the outlet flow rate increased and
27
water level decreased (9/22-9/30), the HRT was reduced to 0.5 days with a standard
deviation of 0.0 days.
Table 2.3 Hydraulic retention time (HRT) calculation components for critical period.
Pilot Wetland HRT
Date
9/1/09
9/2/09
9/3/09
9/4/09
9/5/09
9/6/09
9/7/09
9/8/09
9/9/09
9/10/09
9/11/09
9/12/09
9/13/09
9/14/09
9/15/09
9/16/09
9/17/09
9/18/09
9/19/09
9/20/09
9/21/09
9/22/09
9/23/09
9/24/09
9/25/09
9/26/09
9/27/09
9/28/09
9/29/09
9/30/09
Flow In
3
(m /hr)
Flow Out
3
(m /hr)
Water Depth
(cm)
HRT (days)
14.0
3.9
36.6
1.8
13.9
3.6
37.6
2.0
13.5
1.1
40.8
2.8
13.4
0.8
43.1
3.2
13.7
0.9
43.8
3.1
13.9
1.5
44.1
2.9
13.9
1.5
45.0
2.9
13.9
1.6
45.5
2.9
11.3
1.7
43.6
3.3
12.0
0.5
44.9
3.8
12.1
1.4
45.7
3.4
12.3
10.4
37.5
1.4
12.4
6.8
29.3
1.4
12.4
4.0
32.3
1.7
12.5
2.5
38.6
2.4
12.5
3.0
41.5
2.5
12.5
3.3
43.3
2.5
12.3
3.8
43.5
2.4
12.3
5.9
42.3
2.0
12.3
11.7
33.2
1.2
12.4
11.0
22.2
0.8
12.5
9.8
15.6
0.6
12.6
9.2
12.5
0.5
12.7
8.8
11.7
0.5
12.5
8.6
11.7
0.5
12.5
8.5
11.7
0.5
12.5
8.6
12.9
0.5
12.5
8.6
12.3
0.5
12.4
8.6
12.6
0.5
12.4
8.5
13.0
0.5
28
Decreased HRT did not result in less thermal treatment. Between 9/1 and 9/19, the
average effluent temperature treatment was 1.1° C, and when HRT decreased
between 9/22 and 9/30, the average temperature treatment was 1.3° C. This increase
in observed treatment for shorter HRTs suggests that inlet temperatures were already
near the wetland balance temperature (the temperature at which the no more treatment
occurs) and that longer HRTs would not increase treatment observed in the outlet.
In October 2009, the WWTP provided data from a Discharge Monitoring Report
(DMR) that showed the daily maximum temperature of effluent leaving the plant and
being transported to a nearby storage lagoon. Comparing this data to inlet and outlet
daily maximum temperatures, it can be seen that the majority of the effluent
temperature treatment occured after leaving the plant and before arrival at the wetland
inlet (see Figure 2.10 and Table 2.4). The average difference between daily
maximum temperatures at the DMR location and the wetland inlet was 4.1° C
(compared to -1.2° C from inlet to outlet, using total average temperatures). Thus, it
appeared that most of the temperature reduction occurred in the storage lagoon while
the water awaited delivery to the wetland.
Water Temperature (°C)
28
DMR Value
Inlet
Outlet
24
20
16
12
9/1/09
9/8/09
9/15/09
9/22/09
9/29/09
Figure 2.10 Daily maximum temperatures during critical period, collected from
continuous sensors.
29
Table 2.4 Daily maximum temperatures for DMR, inlet, and outlet locations.
WWTP Effluent Temperatures
Date
9/1/2009
9/2/2009
9/3/2009
9/4/2009
9/5/2009
9/6/2009
9/7/2009
9/8/2009
9/9/2009
9/10/2009
9/11/2009
9/12/2009
9/13/2009
9/14/2009
9/15/2009
9/16/2009
9/17/2009
9/18/2009
9/19/2009
9/20/2009
9/21/2009
9/22/2009
9/23/2009
9/24/2009
9/25/2009
9/26/2009
9/27/2009
9/28/2009
9/29/2009
9/30/2009
DMR Daily
Max (C°)
Inlet Daily
Max (C°)
Outlet Daily
Max (C°)
23.67
20.09
19.57
23.95
20.04
19.26
23.64
19.8
19.15
23.45
19.9
18.48
22.85
18.85
17.91
22.30
19.35
17.53
22.37
18.61
16.89
22.51
18.33
16.60
22.82
18.71
16.55
23.23
19.3
17.08
23.55
19.56
18.36
23.59
19.49
19.86
23.14
19.18
19.55
23.21
19.33
18.69
23.40
19.47
18.65
23.18
19.35
18.27
23.33
19.18
17.89
24.29
18.87
17.20
22.85
18.47
16.91
22.63
18.07
16.72
22.59
18.61
18.05
22.75
18.04
19.57
22.87
18.21
19.67
22.68
18.23
18.55
22.68
18.3
19
22.59
19.33
18.96
22.47
18.16
18.53
21.84
18.04
16.67
21.56
17.02
15.62
21.41
16.38
15.22
Average Treatment from DMR location to Inlet
DMR - Inlet
Diff. (C°)
-3.58
-3.91
-3.84
-3.55
-4.00
-2.95
-3.76
-4.18
-4.11
-3.93
-3.99
-4.10
-3.96
-3.88
-3.93
-3.83
-4.15
-5.42
-4.38
-4.56
-3.98
-4.71
-4.66
-4.45
-4.38
-3.26
-4.31
-3.80
-4.54
-5.03
= -4.1
30
This observation provides a possible explanation of why more temperature treatment
was not realized in the pilot wetland, since effluent temperatures had already come
down toward the wetland balance temperature by several degrees by the time of
arrival at the inlet. Had effluent temperature entered the wetland around 4° C higher,
temperature reduction would have occurred across the entire length of the wetland
(which was not observed with the DTS study) and overall temperature treatment
could reasonably have been assumed to be greater. Further, observation of the DMRinlet differences also demonstrated the potential feasibility of using storage lagoons to
treat effluent temperatures in the future. According to Kadlec and Wallace (2008)
storage lagoons are able to achieve near-wetland temperatures.
2.4.2
Spatially Detailed Observations
DTS monitoring of temperature treatment during a 4-day study from 8/29 – 9/2/09
revealed more detailed information about processes occurring within the wetland.
Figure 2.11 is a compilation of 72 hrs of continuous, 10-minute data averaged across
all four transects. Marginal temperature reduction is observed in the first (northern)
half of the wetland, while effluent proceeded through the second half with little
virtually no temperature change.
Figure 2.11 shows the middle deep zone at 24 m from the beginning of the profile.
Here, a cold depression in the temperature profile appears as the cable passed along
the ground surface at a greater water depth. This cold water depression is most
apparent at 1800 hours, indicating that the deep zone, which was intended for cold
water mixing, was mostly stratified during the day. In the event that colder water
passed across the top of the deep zone at night (as the 00:00 profile suggests might
have occurred) mixing would have been activated as colder, denser water sank and
warmer, less-dense water rose.
31
Longitudinal Temperature Profile
21
20.5
Middle deep zone
Temperature (C)
20
00:00
06:00
12:00
18:00
19.5
19
18.5
18
17.5
17
0
5
10
15
20
25
30
35
Distance (m from north deep zone)
40
45
Figure 2.11 A longitudinal profile of the wetland calculated as the average of all four
transects over a 72-hour period (8/30 – 9/2/09). Notice the appearance of a cold
depression representing the middle deep zone at 1800 hours.
Figure 2.12 also demonstrates the location and temperature processes of the middle
deep zone. In this figure, which represents the variance of the temperature profile
over 72 hours, the deep zone had the lowest variance throughout the day. This further
suggests that little mixing occurred, and the deep zone often behaved as a stratified
column of water. The variance plot also shows that the range of water temperatures
increased as the water passed through the northern and southern shallow zones (0-22
m and 27-49 m).
32
Std. Dev. Average of Transects
0.8
0.75
Middle deep zone
of Temperature
0.7
0.65
0.6
0.55
0.5
0.45
0.4
0
5
10
15
20
25
30
35
40
Distance (beginning from the north; m)
45
50
Figure 2.12 Temperature variance in the longitudinal profile over 72 hours. The
middle deep zone is represented as the area with least variance around 25 m.
Inlet heat waves due to diel temperature cycles in the storage lagoon were observed in
the inlet temperature data. Initially, these heat waves were considered to propagate
through the entire length of the wetland and be observable in the outlet temperature.
However, the DTS study, which provided the actual wetland temperature profile
along the flow path, does not support this perspective. Figure 2.13 shows the average
temperature profile—obtained from combining the four transects—plotted as point
locations over 3 days. Each line on the plot represents one of 49 distinct observation
nodes across the profile. Essentially, heating and cooling of the entire wetland is seen
all at once, since the transects cover most of the length and width of the submerged
area. The figure demonstrates that daily heating and cooling occurred collectively
throughout the wetland (within several hours, depending on location). Diel pulses of
heated water, which would be expected to most visible as peaks at night, are not
33
observed, indicating that inlet heat waves were quickly absorbed by the wetland
system.
20
19.5
Temperature (C)
inlet
outlet
19
18.5
18
17.5
17
8/31/09
9/1/09
9/2/09
9/3/09
Figure 2.13 All points along the wetland longitudinal temperature profile. Over
several diel cycles, the wetland showed that it primarily heats and cools collectively.
The longitudinal temperature profile was obtained by averaging all cable transects at
each distance along the length of the wetland.
Temperature treatment through the vegetated north half of the wetland, as reported by
point temperature loggers, was unclear. Temperatures from the ―East S. Midzone‖
logger located north of the middle deep zone appeared to indicate more effective
thermal reduction and less diel fluctuation of effluent after passing through the first
half of the wetland (see Figure 2.14). Temperature variance across each longitudinal,
72-hour transect of the DTS study were plotted. Figure 2.15 shows the pattern of
temperature variance corresponding to particular locations in the wetland. The
irregularity in daily temperature ranges throughout the wetland suggests that point
measurements within the wetland may not be representative of larger wetland areas.
34
Figure 2.14 Inlet, outlet, and East S. Midzone 10-minute temperatures at the
beginning of the September critical period.
Four Longitudinal Transects
1.4
WW
WE
EW
EE
Std. Deviation (C)
1.2
1
0.8
0.6
0.4
0.2
0
0
5
10
15
20
25
30
35
Distance (m from north deep zone)
40
45
Figure 2.15 Temperature variance observed over 72 hours in all four transects.
35
2.5
Summary and Conclusions
The objective of this study was to assess the pilot wetland efficacy for effluent
temperature reduction during the 2009 operational period. Based on the inlet and
outlet temperature loggers, the wetland showed marginal treatment for most of the
study, with an average cooling of 1.2°C realized during the critical month of
September. Reducing the HRT from 2.5 to 0.5 in mid-September showed no
detrimental effect on temperature treatment. This is attributed to the effluent entering
the wetland very near to wetland balance temperature. In addition, it was determined
that substantial effluent cooling occurred in the WWTP storage lagoon before
entering the wetland. As a result, less temperature reduction was observed in the
treatment wetland; however, the feasibility of using lagoons for effluent cooling—at
least to a certain level—was demonstrated.
The DTS fiber optic study produced high spatial resolution results that led to several
insights. First, virtually all of the temperature treatment (or slope in the temperature
profile) occurred in the first half of the wetland, showing that the water had indeed
reached its balance temperature. Second, for most of the day the middle deep zone
was ineffective in mixing and stratified by temperature-dependent densities. Third,
inlet heat waves were absorbed within the first 25 meters and the wetland heated and
cooled as a collective unit. Lastly, spatially-sensitive variations in observed
temperature treatment showed that point measurements, such as logger ―East S.
Midzone‖, can misrepresent the treatment occurring over larger areas.
In consideration of future effluent treatment at the WWTP, the data presented in this
study demonstrated that approximately 5°C temperature reduction was achieved
between leaving the WWTP main facility and exiting through the pilot wetland outlet.
Since most of this reduction occurred in the storage lagoon, the thermal treatment
capacity of the wetland is largely unknown. Effluent entering the wetland was
slightly cooled for most of the summer, and during the DTS study, reached balance
temperature by the middle deep zone. If further understanding about the wetland
36
system capacity is desired, effluent entering the wetland would need to be several
degrees warmer than the wetland balance temperature.
2.6
Acknowledgements
We thank Jason Smesrud at CH2M HILL for closely working together on this
research, and the City of Woodburn and its Wastewater Treatment Plant staff—
especially Curtis Stultz, Mike Arellano, Jason Garner, and Ramon Garcia—for their
professional assistance and cooperation.
2.7
References
Dakin, J. P., D. J. Pratt, G. W. Bibby, and J. Ross (1985) Distributed optical fiber
Raman temperature sensor using a semiconductor light-source and detector,
Electron. Lett., Vol. 21(13), pp. 569–570, doi:10.1049/el:19850402.
Faulwetter J.L., Gagnon, V., Sundberg, C., Chazarenc, F., Burr, M.D., Brisson, J.,
Camper, A.K., and O.R. Stein (2009) Microbial processes influencing
performance of treatment wetlands: a review, Ecol. Eng. Vol. 35, pp. 987–
1004.
Freifeld, B.M., Finsterle, S., Onstott, T.C., Toole, P., and M. Pratt (2008) Ground
surface temperature reconstructions: Using in situ estimates for thermal
conductivity acquired with a fiber-optic distributed thermal perturbation
sensor. Geophys. Res. Lett., Vol. 35: L14309.
Healy, Robert P., and Mark F. Madison, CH2M HILL. Planning Document for the
Selection of Temperature and Ammonia Reduction Alternatives. Rep. 2006.
Print.
Kadlec, R.H. and K.R. Reddy, Temperature effects in treatment wetlands, Water
Environ. Res. 73 (2001), pp. 543–557.
Kadlec, R.H. (2006) Water temperature and evapotranspiration in surface flow
wetlands in hot arid climate. Ecol. Eng. Vol. 26 (4), pp. 328–340.
Kadlec, R.H., and S.D. Wallace (2008) Treatment Wetlands, second ed. CRC Press,
Boca Raton, FL.
Kadlec, R. H. (2009) Wastewater treatment at the Houghton Lake wetland:
Temperatures and the energy balance, Ecol. Eng. Vol. 35 (9), pp. 1349-1356.
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Kurashima, T., T. Horiguchi, and M. Tateda (1990) Distributed-temperature sensing
using stimulated Brillouin-scattering in optical silica fibers, Opt. Lett., Vol. 15
(18), pp. 1038–1040.
Picard C.R., Fraser, L.H., and D. Steer (2005) The interacting effects of temperature
and plant community type on nutrient removal in wetland microcosms, Biores.
Technol. Vol. 96, pp. 1039–1047.
Selker, J.S., The´venaz, L., Huwald, H., Mallet, A., Luxemburg, W., Van de Giesen,
N., Stejskal, M., Zeman, J., Westhoff, M., and M.B. Parlange (2006a)
Distributed fiber-optic temperature sensing for hydrologic systems. Water
Resour. Res., Vol. 42: W12202.
Selker, J., Van De Giesen, N., Wethoff, M., Luxemburg, W., and M.B. Parlange
(2006b) Fiber optics opens window on stream dynamics. Geophys. Res. Lett.,
Vol. 33: L24401.
Tyler, S., Burak, S., McNamara, J., Lamontagne, A., Selker, J., and J. Dozier (2008)
Spatially distributed temperatures at the base of two mountain snowpacks
measured with fiber optic sensors. J. of Glac., Vol. 54 (187).
Tyler, S. W., J. S. Selker, M. B. Hausner, C. E. Hatch, T. Torgersen, C. E. Thodal,
and G. Schladow (2009) Environmental temperature sensing using Raman
spectra DTS fiber-optic methods. Wat. Resour. Res., Vol. 45, W06413,
doi:10.1029/2008WR007551.
US Bureau of Reclamation. 2009. AgriMet—The Pacific Northwest Cooperative
Agricultural Weather Network. http://www.usbr.gov/pn/agrimet/.
Westhoff, M.C., Savenije, H. H. G., Luxemburg, W. M. J., Stelling, G. S., van de
Giesen, N. C., Selker, J. S., Pfister, L., and S. Uhlenbrook (2007) A
distributed stream temperature model using high resolution temperature
observations. Hydrol. Earth Syst. Sci., Vol. 11: 1469–1480.
Werker, A.G., Dougherty, J.M., McHenry, J.L., and W.A. Van Loon (2002)
Treatment variability for wetland wastewater treatment design in cold
climates, Ecol. Eng. Vol. 19 (1), pp. 1–11.
Wittgren, H.B., and T. Maehlum (1997) Wastewater treatment wetlands in cold
climates. Wat. Sci. Tech. Vol. 35 (5), pp. 45–53.
38
3
INFILTRATION CHARACTERIZATION OF A CONSTRUCTED
WETLAND FOR WASTEWATER TREATMENT
Chris Gregory, John S. Selker, Ryan Stewart, Daniel Moreno
Department of Biological and Ecological Engineering
Oregon State University, Corvallis, OR 97331
For Submission to Hydrology and Earth System Sciences
39
3.1
Abstract
This study characterizes the infiltration of an unlined surface flow wetland observed
in the summer and early fall of 2009. The wetland was approximately 0.15 ha and
was constructed in a river floodplain using native silty clay loam from the Wapato
series classification. The purpose of the wetland was to demonstrate the feasibility of
using treatment wetlands for temperature and ammonia reduction in wastewater
effluent. Infiltration was determined as the daily residual of a wetland water budget.
Infiltrative variability was characterized with a distributed temperature sensor (DTS)
by applying heat pulses to a subsurface fiber optic cable. Infiltration losses exceeded
outflow losses for most of the study, but steadily decreased over time. Infiltrative
variability was within a factor of 2 and also decreased over time. Soil clogging
processes, settling, and instrument error are offered as reasonable explanations.
3.2
Introduction
The City of Woodburn’s Wastewater Treatment Plant (WWTP) is currently
investigating natural alternative systems for improving the quality of its effluent.
Based on the current limits for allowable discharge into the Pudding River outlined in
the WWTP’s NPDES permit, temperature and ammonia restrictions will be annually
exceeded by 2020 in the summer and early fall (Healy and Madison, 2006).
In order to avoid future NPDES violations, the City of Woodburn has constructed
several pilot-scaled natural systems to assess their potential for improving wastewater
quality and inform decisions regarding future WWTP operations. One of the pilot
systems, a 0.15 ha free surface flow wetland, was developed in the floodplain of the
Pudding River near the WWTP site. The wetland was designed to reduce effluent
temperature and ammonia levels before reaching the nearby Pudding River.
Monitoring of wetland temperature treatment was conducted in 2009 and has been
presented in chapter 2.
40
Further, monitoring wetland infiltration was also necessary to understand the pilot
system performance. The surface flow wetland was constructed with native
floodplain soil material and expected to exhibit substantial leakage into the
underlying silty sand aquifer. Pre-existing drainage tiles throughout the floodplain in
unknown locations were suspected to make preferential drainage pathways an
additional concern. Consequently, for designers and city officials considering the
impact of larger wetlands at the WWTP site, assessment of total infiltration and
infiltration variability in the pilot wetland was critical to understanding the local
area’s hydraulic potential.
The objective of this study was to characterize infiltration in the pilot wetland during
operations in the summer and early fall of 2009. System-wide infiltration was
calculated using a wetland water budget, and additional information about infiltration
variability was obtained using a heat pulse method on a distributed fiber optic cable
located approximately 25 cm below ground. Temperature from the fiber was
collected with distributed temperature sensor (DTS) systems. Based on the findings
of this research, conclusions about the infiltration characteristics observed were
passed on to those responsible for potential wetlands expansion at the WWTP.
3.2.1
The Wetland Water Budget and Infiltration
Understanding the flow through a treatment wetland can begin with a simplified
determination of water inputs and outputs. While assessing the actual rates of these
processes can be difficult and commonly imprecise, they nonetheless comprise the
broader framework for understanding the hydrology of the system. Figure 3.1 shows
the inputs and outputs flows involved in the wetland water budget.
41
Figure 3.1 Components of the wetland water budget. (adapted after Kadlec and
Wallace, 2008)
The main processes contributing water to the wetland, referred to as inputs, include
the volumetric inflow coming from the WWTP, potential stream contributions or
catchment runoff, local groundwater discharges into the wetland, and precipitation.
In the present study of the Woodburn pilot wetland, constructed berms around the
perimeter of the wetland cell prohibited catchment runoff, and the nearby Pudding
River was blocked from entering the floodplain by a temporary culvert plug during
the operation period in the summer. In addition, the local groundwater table under
the wetland sat well below the ground surface and did not contribute to surface water
flow. The input components were then reduced to precipitation, which was extremely
little in the summer and early fall, and volumetric inflow.
42
The processes contributing to the water outputs include volumetric surface outflow,
groundwater recharge, or infiltration, lateral bankloss through perimeter berms, and
evapotranspiration. Depending on the type of wetland, its vegetation, climate,
geology and construction, the relative magnitude of each output can vary greatly. For
example, in a surface flow wetland that has been lined with 30 cm of compacted clay
to prevent mixing with underlying groundwater, infiltration may be insignificant and
surface outflow may account for most of the exiting water. However, in the case of
an unlined surface flow wetland, such as at the Woodburn WWTP, infiltration may be
comparable or at times even exceed outflow.
Lateral bank losses can be a significant infiltration component where the perimeterto-area ratio of the wetland is relatively large. In this case, hydraulic gradients
through the confining banks may be much greater than vertical infiltration through the
bottom of the wetland basin, contributing to higher rates of lateral infiltration at these
locations. Lateral bankloss becomes less significant when the water level in the
wetland is lowered and the hydraulic gradients through the banks are reduced.
Evapotranspiration depends on the climate, season and vegetation in the wetland.
Often, evapotranspiration can be estimated by using atmospheric data from national
weather stations and applying a crop-based conversion coefficient.
To close the water budget, the volumetric change in wetland water storage is needed.
This term can be related to the water depth if the internal wetland geometry is
uniform or a detailed survey of the internal bathymetry has been conducted. In many
natural wetlands, the bathymetry of the wetland is quite complex, owing to irregular
landscape features as well as changing depositional processes and thicknesses of
accumulating sediment. This makes relating the water depth at a monitored location
to volume of water in the entire wetland system quite challenging. However, many
constructed wetlands operate with rather simple geometries that allow accurate
estimation of the total volume stored.
43
In wetlands that are used as advanced treatment to polish the water quality and where
there is no perceived threat to groundwater contamination, infiltration may be allowed
without the use of a restrictive lining. Leaky wetland systems may also be opted for
when the infiltrating water is expected to be diluted through discharge into a nearby
river (Kadlec and Wallace, 2008).
The processes that govern groundwater infiltration are complex, as issues arise out of
the unique placement, hydrogeology, water quality, vegetation and operation of any
particular wetland. In a wetland with significant leaking and a relatively shallow
water table, infiltration below the wetland may saturate the underlying porous media
and begin to mound on the piezometric surface. If mounding is large enough, the
hydraulic gradient of infiltration will be reduced, leading to lower infiltration rates
over time. However, confining layers in the underlying subsurface may complicate
this process leading to mounding at shallower depths and/or lateral flow away from
the local piezometric surface.
Infiltration through treatment wetlands has also been shown to vary significantly
based on the quality, loading rate and duration of applied influent (Kadlec, 2008). In
low quality wastewater with high total suspended solids (TSS), biological oxygen
demand (BOD), nitrogen and ammonia levels, clogging in the top horizon of wetland
soil is well established (Van Cuyk, 2001; Blazejewski, 1997; Kadlec and Wallace,
2008). Formation of a clogging layer is especially acute in horizontal subsurface flow
wetlands and vertical infiltration wetlands (Knowles, 2009; Langergraber, 2003),
however the same processes may occur in leaky surface flow wetlands that operate
similarly to recharge basins (see Bouwer and Rice, 1989, on clogging processes in
recharge basins).
The clogging of wetland soil surfaces has been attributed to a number of contributing
processes. According to the literature, the main causes are the grain distribution and
pore sizes of the bed material, deposition of suspended solids in the soil pores,
44
accumulation of organic material resistant to microbial degradation in the soil biomat
formation of microbial biofilms on the soil surfaces, development of plant roots and
rhizomes that occupy pore volume, and chemical precipitation and deposition in the
pore spaces (Blazejewski, 1997; Kadlec and Wallace, 2008). These processes
effectively reduce the hydraulic conductivity of the wetland by decreasing the
porosity of the top layer of soil. In this situation, the infiltration rate in the wetland
becomes limited by the hydraulic conductivity of the clogging layer. Further,
hydraulic conductivity has been shown to be extremely sensitive to porosity,
decreasing by about a factor of 10 when porosity is reduced by one-third (Kadlec and
Wallace, 2008).
Taken together it is apparent that prediction of the spatial distribution of percolation
under a wetland is bound to be imprecise. We therefore decided to directly measure
spatial distribution of percolation using fiber optic temperature sensing.
3.2.2
DTS and the Heat Pulse Method
Distributing Temperature Sensing (DTS) background, theory, and system components
have already been discussed in some detail in chapter 2. A brief review is provided
here.
DTS systems were first developed two decades ago and use optical fibers as
temperature sensors (Dakin et al., 1985; Kurashima et al., 1990). High frequency
light transmissions are emitted by DTS systems through the optical fibers while an
optical sensor records the frequencies and amplitudes of backscattered photons. The
arrival time of returning backscatter is recorded by the DTS, while Brillouin and
Raman scattering principles are applied to the backscattered photons to calculate fiber
temperatures. Based on the arrival time data and the speed of light in the optical
fiber, the calculated temperatures are associated with positions on the optical fiber.
The result is a detailed temperature profile across the length of the fiber with
45
accuracies approaching 0.01°C and spatial resolution up to 0.25 m (Selker et al.,
2006).
Methods for extracting soil properties and water content through heated probes have
been well established (Byrne et al., 1968; Mori et al., 2003; Tarara et al., 1997).
These methods are based on quantified heat inputs being applied to porous media and
the resulting thermal response being monitored by temperature sensors. In singleprobe configurations, the heating component and temperature sensor are co-located
on the same probe device. In multi-probe configurations, one probe typically serves
as the heated element while the other probes monitor the thermal response of the
media at fixed distances from the heated element (Basinger et al., 2003; Bristow et
al., 1994). As heating methods have become more useful for determining soil
properties and water content, numerous techniques for quantifying water flux with
heated probes have also been investigated (Hopmans et al., 2002; Wang et al., 2002;
Mori et al., 2005).
More recently, several studies have incorporated fiber optic cables into single-probe
heat pulse methods. These studies have utilized the protective metallic jackets found
on many fiber optic cables as electrical resistors, capable of heating the cable
uniformly across its length. DTS systems were then used to extract temperature
profiles from the cable to monitor its thermal response to the heating based on its
location of deployment. Weiss (2003) and Perzlmaier et al. (2004) both investigated
thermal conductivities and water contents of soils using heated fiber optic cables.
Their methods involved cable heating for an extended period of time, followed by
calibration equations fitted to the slope and intercept of resulting thermal responses.
Sayde et al. (2009) followed this work with an alternative approach for calculating
soil moisture content. His method used the integration of the total change in fiber
temperature to distinguish between soil moisture contents.
46
Several studies have also demonstrated the capability of DTS fiber optic applications
to measure water flux in porous media. Johansson et al. (2004) and Velasquez et al.
(2007) used fiber optics in the monitoring of localized seepage in embankment dams
and earthen structures. Their techniques were passive measurements that relied on
temperature gradients to reveal seepage, and where feasible, quantify flux.
Perzlmaier et al. (2004, 2006) investigated the use of actively heated fiber optics for
determination of seepage velocity. They applied numerical methods to laboratory and
field data for total rise in temperature, and found that analytical and DTS results were
quite agreeable (see Perzlmaier et al., 2004). The approach used in this study for
investigating relative seepage variability largely followed the methods developed by
Perzlmaier et al. (2004, 2006) in respect to monitoring dam leakage.
3.3
Materials and Methods
3.3.1
Site Description
A more complete overview of the location, climatic conditions, operational
components and vegetation of the pilot wetland can be found in the Materials and
Methods section of chapter 2. In general, the wetland was located in the floodplain of
the Pudding River near Woodburn, Oregon, within larger context of the Willamette
Valley (see Figure 2.2 for a map view of the site). The wetland soil material was
classified as silty clay loam in the Wapato series, which locally overlaid a shallow
groundwater aquifer that discharged into the Pudding River. Woodburn’s WWTP
delivered water to the wetland from an uphill storage lagoon, and the hydraulic
operation was designed to maintain a 2-day hydraulic retention time (HRT), which
translated to a water depth of about 40 cm.
In addition, numerous pre-existing agricultural drain tiles intended to quickly drain
the floodplain underlie the surrounding land, providing significant opportunity for
preferential drainage pathways. Little certainty exists about the locations and
orientations of these drain tiles (which were buried approximately 2 m underground),
however several drain tiles directly beneath the wetland were unearthed and plugged
47
in the summer of 2008. The success of this effort to seal the wetland from excessive
tile drainage was investigated in this study
3.3.2
Instrumentation
Two Onset HOBO® U-20 submersible water level loggers, housed in three-foot,
drive-tip piezometers, were placed in the north and south ends of the wetland. The
piezometers were manually driven halfway down (1.5 feet) into both the north and
south deep zones. The U-20 loggers recorded continuous absolute pressures averaged
over 10-minute intervals. Details about the treatment of the data and water level
calculations were presented in the Materials and Methods section of chapter 2.
Two additional HOBO® U-20s located in nearby piezometers were utilized to
interpret the hydrologic response of the shallow aquifer in surrounding areas. These
U-20 loggers were operated continuously and averaged over 15-minute intervals.
Two Signet 2552 Metal Magmeter flow sensors (Schaffhausen, Switzerland) were
installed in the inlet and outlet locations of the wetland pipe irrigation system. The
first sensor monitored flow entering the wetland through the inlet control pipe. The
second sensor recorded the only surface flow leaving the wetland through an outlet
pipe. Campbell Scientific CR200-series dataloggers recorded continuous flow from
these sensors based on 5-minute flow averages. Further information on the
calibration procedure undertaken with these flow sensors can be found in chapter 2.
Two Raman-based DTS systems were used in fiber optic temperature collection—a
SensorTran 5100 M4 and a Sensornet Oryx. Data was collected on the SensorTran
using 1-minute integration times with 0.5 m spatial resolution. The Sensornet Oryx
was used with 1-minute integrations and 1 m spatial resolution.
Calibration of the DTS systems were explored using both internal (involving the DTS
operating configuration) and external (involving post-processing data alteration)
48
procedures. For data collection with the SensorTran DTS, ice-slush baths kept
around 0° C were placed at the ends of each cable segment, while internal
adjustments to the calibration coefficients were made within the DTS operating
system to match field observations. Light attenuation at the junction of fiber splices
necessitated calibration for each continuous fiber segment between splices. After
calibration coefficients were assigned for all segments, the DTS produced fairly
accurate results (within about 1° C).
With actual temperatures of the ice-slush baths as well as warm-water baths recorded
with a high-precision thermometer during many data collections, an external
calibration procedure was developed to rectify the data to within 0.1° C (see
Appendix A). This calibration procedure took the ―roughly‖ calibrated data from the
internal DTS adjustments, then made offset, attenuation, and gain corrections based
on field data (see Appendix Figures A.1 through A.8). However, for applications of
the heat pulse method that are concerned with changes in temperature rather than the
finite accuracy of absolute temperature, this kind of external calibration was found
unnecessary. Thus, data collection in later work with the Sensornet Oryx DTS was
taken with minimal internal calibrations and no external calibrations.
3.3.3
Fiber Optic Installation
Over one kilometer of fiber optic cable was strategically emplaced in the top 30 cm of
the wetland soil. The cable emplacement was accomplished using a custom steel
plow that was designed specifically for this installation. The plow consisted of a
large steel base plate that rested flush with the ground surface, a smaller steel plate
that had been inserted through and welded to the base plate, serving as the plow
blade, and a two-tiered metal pipe rack extending vertically above the base plate that
was used to hold up to four reels of cable at a time (see Appendix Figure C.2). The
plow blade was welded to the base plate at a 30 degree angle from perpendicular so
that after passing through the ground, the resulting crack would be aided by gravity in
re-sealing. Four grooves were reamed into the plow blade, starting from the top edge
49
where the fiber optic cables would enter, and then continuing down the side of the
blade and out the back edge where the cables would exit. Four stainless steel pipes
were then inserted into each of the grooves to guide the cables into and out of the
plow blade. Plow advancement was accomplished by attaching the front end of the
plow to the back end a tractor by a sufficiently thick steel cable, and then driving the
tractor forward. The leading edge of the base plate was bent upward 30 degrees from
horizontal to reduce friction with ground surface and the likelihood of vegetation
snags. In addition, the reel racks were designed to incur minimal friction with the
reels, allowing the cable to unwind freely with advancement of the plow.
In regards to the fiber optic layout within the wetland, two large U-shaped loops were
plowed in both the east and west sections of the wetland (see Figure 3.2). Each ―U‖
loop consisted of four cables, each about 130 m in length, simultaneously being
plowed into the ground at four different depths—10, 20, 25, and 30 cm. (these depths
are relative to the plow blade; vertical depths accounting for 30 degree plow blade
angle are closer to 8.7, 17.3, 21.7, and 26 cm.) The installation resulted in the
emplacement of eight separate segments of cable, all approximately 130 m in length
(see Appendix Figures C.3 and C.4). In order to collect temperature data from all of
the segments at once, the optical fibers were joined together through a series of fusion
splices that ultimately created a single fiber. Since the cables in the study were
―duplex‖ (that is, they contained two fibers) the DTS collected data from both fibers
in each cable. Therefore, the sensor length was effectively doubled by utilizing both
fibers in the cables, resulting in duplicate temperature measurements for each
geospatial location. In all, 16 splices were made across 1025 m of cable, producing a
2050 m fiber length.
To reference specific cables segments, nomenclature was developed based on
north/south and east/west divisions. The first division reference refers to either north
or south of the middle deep zone. The second reference is either east or west of the
middle berm. The last division reference refers to the east or west sides of the
50
shallow area. For example, ―NEW‖ refers to the cables north of the middle deep
zone, east of the middle berm, and on the west side of the shallow area (closest to the
middle berm).
NWW
NWE
NEW
NEE
SWE
SEW
SEE
Flow Direction
SWW
Figure 3.2 Location of sensors and fiber optic cable depths in pilot wetland. U.S.
customary units are used for length dimensions, corresponding to wetland blueprints.
Quadrant nomenclature is shown for each of eight subsurface cable segments.
3.3.4
Components of a Wetland Water Budget
A wetland water budget can be represented by the equation:
51
Flow In + Precipitation = Flow Out + Infiltration + ET + Δ Storage
Eq. 3.1
The following discusses the data collected and methods used for quantification of
each term in the wetland water budget equation.
Flow In
Flow entering the wetland was recorded as 5-minute averages by a Magmeter flow
sensor located at the inlet control pipe. This flow value, in gpm, was then converted
to a loading rate in cm/day by summing the total volume in, converting from gallons
to cubic meters, and then dividing by the area of the wetland. The wetland area was
determined using field-validated blueprint dimensions of wetland length and width,
accounting only for the internal areas covered in water and one additional foot of
horizontal berm area at each boundary (Figure 3.3).
Surface water
area
Figure 3.3 Blueprint of pilot wetland (in US customary units). Surface water area
used for loading rate calculations is represented in blue, excluding the middle and
perimeter berms.
52
The length and width dimensions used in the area calculation were:
Wetland water area = (173 ft x 77 ft) - (155 ft x 4 ft) = 12701 ft2 = 1180 m2
where the first term represents the submerged interior area and the second term
represents the above-water berm area.
Precipitation
Daily precipitation values were obtained online from the USBR AgriMet weather
station in Aurora, Oregon (station ARAO). These values, given in inches, were
converted to cm and treated as an additional loading rate term in cm/day.
Flow Out
Flow leaving the wetland was recorded with a Magmeter flow sensor similarly to the
flow coming in. The sum of the volume leaving each day was divided by the wetland
area to convert to a rate of cm/day.
Evapotranspiration
Daily evapotranspiration (ET) values were calculated using Aurora, Oregon AgriMet
weather station data (station ARAO). Output from the Aurora AgriMet station is ETr,
an alfalfa reference, and needs to first be converted to a grass reference, ETo. Using
an AgriMet crop coefficient curve for lawn/turf (essentially reference grass
conditions) the following conversion was applied:
ETo = 0.80 x ETr
Eq. 3.2
To calculate crop ET, the following equation was used:
ETc = Kc x ETo
Eq. 3.3
where ETc refers to the crop ET, and Kc, refers to the crop coefficient. Kc was
obtained from FAO document 56 for cattails and bulrushes at most 2 m tall, using the
53
mid-season value of 1.20. The daily value of ETc was converted from inches and
considered as a daily rate of cm/day.
Change in Storage
To account for changes in water storage within the wetland, daily average water
levels were determined from hourly pressure transducer data. These averages were
then compared across consecutive days to determine changes in water level height
and given units of cm/day.
Infiltration
With all other components accounted for, infiltration was calculated as the residual of
the water balance equation:
Infiltration = Flow In + Precipitation – Flow Out – ET – Δ Storage
Eq. 3.4
The continuous data for the above components therefore provides daily infiltration
rates through time in cm/day.
3.3.5
Spatially Distributed Infiltration Rates
In an effort to spatially determine relative variability in infiltration rates, a DTS
system was used in conjunction with a subsurface fiber optic cable that was heated for
various lengths of time. The cable was a Brusteel (Brugg Cable, Brugg, Switzerland)
4FG5, duplex, multimode cable located at approximately 25 cm depth (see Figure
3.2). Heating was accomplished by connecting 220 V to the cable’s interior steel
jacket exposed on the ends of each cable segment. Both heated cable segments
(located in the east and west halves of the wetland) had lengths of approximately 105
m. The resistivity of the steel jacket was 440 ohms/km. The total resistance of the
cable, RT, can be calculated as:
RT = R * L = 440 Ω /km * 0.105 km = 46.2 Ω
54
Eq. 3.5
and the heat flux per unit length, qL, can then be determined by:
qL = V2/(Rt *L) = 220 V 2/(46.2 Ω * 105 m) = 9.98 or 10 W/m
Eq. 3.6
The following equation, taken from Perzlmaeir et al. (2004) after Wagner (1998),
relates change in temperature to the heat flux applied to a coated cylinder:
Eq. 3.7
where
= total change in temperature from heat pulse (K)
= heat flux per unit length (W/m)
= thermal conductivity of coating (Wm-1K-1)
= outer radius of coating (m)
= inner radius of coating (m)
= heat transfer coefficient
From the data obtained by the DTS system for a one-hour heated period, ΔT was
determined as the total rise in temperature observed at each meter along the cable.
The starting temperature was calculated at each point as the average of three 1-minute
integrations taken immediately prior to heating. Figure 3.4 shows how ΔT was
determined at each cable location, and Figure 3.5 shows variability in ΔT across a
cable segment. Appendix Figures B.1 through B.6 illustrate several examples of
variable heating in subsurface cable segments using surfaced plots of hour-long heat
pulses.
55
Heated FO Cable Point
Temperature (C)
25
20
∆T
15
10
0
30
60
90
Time (min)
Figure 3.4 Rise in cable temperature, ΔT, observed over heating duration.
Heated FO Cable Segment
Temperature (C)
25
20
15
10
0
30
60
90
Time (min)
Figure 3.5 Variation in cable heating response across a 20 m segment.
56
The manufacturer’s specifications for Brusteel 4FG5 were used for the thermal
conductivity, the outer radius and the inner radius of the coating. Accordingly,
λm = 0.25 Wm-1K-1, ra = 1.9*10-3 (m) and ri = 1.7*10-3 (m).
The dimensionless Nusselt number,
, given for cylinders can be used to express
the heat-transfer coefficient, α, as:
Eq. 3.8
where
D
= diameter of the cylinder (m)
= thermal conductivity of the fluid (Wm-1K-1)
The outer diameter of the cylinder used was 3.8 10-3 m (manufacturer specifications).
Solving the above equations for the heat transfer coefficient, α, gives:
Eq. 3.9
Additionally, the effective Nusselt number for forced convection in a Darcy-flow
regime, taken from Perzlmaier et al. (2004) in following with Fand et al. (1993), can
be written as:
Eq. 3.10
where
ReD =
dimensionless Reynolds number of a cylinder
Preff =
dimensionless Prandtl number
d
=
diameter of the particles (m)
57
The mean particle diameter used for silty clay loam (the Wapato series classification)
was 25 μm (following Muñoz-Carpena and Parsons 2000). Solving for the Reynolds
number gives:
Eq. 3.11
where
v
D
=
pore velocity of fluid (m/s)
=
diameter of the cylinder (m)
=
kinematic viscosity of fluid at temperature (m2/s)
In keeping with the method developed by Perzlmaier et al. (2004), the effective
Prandtl number in the above equation can be solved with:
Eq. 3.12
where keff is the effective thermal diffusivity and can be taken as:
Eq. 3.13
and
λeff = effective thermal conductivity (Wm-1K-1)
ρfl
= density of the fluid (kg/m3)
cp fl = specific heat capacity of the fluid (Jkg-1K-1)
The reference value for kinematic viscosity of water at 12.5 °C is 1.32*10-6 m2/s, the
density of water is approximately 1000 kg/m3, and the specific heat capacity is 4190
58
Jkg K . The effective thermal conductivity used was 1.4 Wm K , corresponding to
-1
-1
-1
-1
the value of saturated Harps clay loam found by Ren et al. (2000). Lastly, the above
equations can be rearranged to solve for pore velocity in the following manner:
Eq. 3.14
To convert pore velocity to Darcy flux (which is helpful for considering infiltration)
the pore velocity is multiplied by the soil porosity. For a silty clay loam the porosity
is approximately 40%. Thus, Darcy flux equals 0.4 times the pore velocity.
3.4
Results
3.4.1
Full Scale Observations
A wetland water budget from 7/25 through 10/9/09 showed consistently decreasing
infiltration rates over a wide range of values (see Figure 3.6). The greatest infiltration
rates were observed at the beginning of the study in July, when calculated Darcy flux
infiltration was 25 to 28 cm/d. Infiltration gradually decreased through August,
despite increasing or comparable hydraulic head in the wetland (see Figure 3.7).
59
Flow In
Evapotranspiration
Precipitation
Storage
Flow Out
Infiltration
40
Flux (cm/d)
30
20
10
0
-10
-20
7/25/09
8/9/09
8/24/09
9/8/09
9/23/09
10/8/09
Figure 3.6 Components of the wetland water budget as fluxes (cm/d).
Changes in water level show some correlation with infiltration (e.g. the drop observed
in Figure 3.7, 8/24 - 9/1) but do not ultimately overcome diminishing rates of
infiltration through time. In mid-September, a substantial reduction of water depth,
from 44 cm to 12 cm, significantly decreased infiltration from about 18 to 8 cm/d
over a period of several days. For the duration of the study lasting through 10/9,
water depth was maintained around 12 cm while infiltration showed a slightly
negative trend, losing about 1 to 2 cm/d over that period.
60
Wetland Water Depth (cm)
Infiltration (cm/d)
Water Depth (cm) or Flux (cm/d)
50
40
Water Depth
30
20
Infiltration
10
0
7/25/09
8/9/09
8/24/09
9/8/09
9/23/09
10/8/09
Figure 3.7 Infiltration rate and water depth during the summer/fall study period.
Notice that the infiltration rate decreases through time, even while water depth
increases (8/1-9/8).
Water level data obtained from pressure transducers in nearby piezometers indicated
that decreasing infiltration in the wetland was not the product of water mounding in
the shallow aquifer. Figure 3.8 shows the relationship between flow application
through the wetland inlet and hydrologic response in the areas of Piezometer 2 (P2)
and Piezometer 3 (P3) (see Figure 2.2 for locations of P2 and P3). In late June and
early July, local water levels peaked indicating that water mounding is near a
maximum, and thereafter declined through the rest of the study. If significant water
mounding was occurring, the water infiltrating from the wetland would experience a
decreased hydraulic gradient. However, the water table surrounding the wetland
declines from July through October, which signifies that the hydraulic gradient from
61
the wetland to the surrounding areas is actually increasing. Thus it is believed that
water mounding is not responsible for observed decreases in wetland infiltration.
P2
P3
Figure 3.8 Water levels in two piezometers nearest the wetland and inlet flow rate.
Notice that water levels peak in June and July and are decreasing August through
September. Variability in P2 and P3 water levels prior to May are assumed to be
related to precipitation and/or local flooding from the Pudding River.
Three suggestions have been devised to explain the observed decrease in wetland
infiltration. First, the sudden reduction in infiltration that occurred in mid-September
was likely due to decreasing the hydraulic gradient within the wetland, as well as a
loss of lateral infiltration through the perimeter berms. The perimeter berms were
responsible for keeping the water in the wetland. At higher water levels, these berms
were submerged under 20 to 30 cm of hydraulic head and could potentially infiltrate
substantial volumes of water in lateral directions with higher hydraulic gradients.
When the water level in the wetland was reduced, as it was in mid-September by
62
about 30 cm, the wetland lost a significant portion of this lateral infiltration, which
contributed to the overall decrease in infiltration.
Secondly, most of the decrease in infiltration caused over the duration of the study
may have been related to organic clogging in the soil horizon. According to Bouwer
and Rice (1989) organic clogging layers commonly develop along the wetted
perimeter of infiltration basins for artificial recharge. Bower and Rice noted that
these clogging layers not only reduce the amount of infiltration that is expected with
increasing water depth, but can actually cause the rate of infiltration to decrease.
Additionally, they observed that algae growth in such basins can form filter cakes on
the basin bottom, which further decreases infiltration. These findings support the idea
that organic clogging due to vegetative growth in the wetland throughout the summer
and fall led to decreased permeability—and thus reduced infiltration—in the wetland
soil. Significant algae growth observed throughout the wetland in July (see Appendix
Figures C.11 and C.12) supports this theory.
Thirdly, it should be noted that Kadlec and Wallace (2008) have reported significant
error in wetland water budgets and suggest using this method with caution.
Therefore, a further possibility proposed here is that the decrease in infiltration was
due to instrument drift in the inlet or outlet flow sensors (or both). Since the
Magmeters reported expected accuracies of approximately ± 2%, instrument error is
not considered likely. However, if the infiltration trends were attributable to error,
drift in the inlet flow sensor seems most plausible since inlet flow rate was usually
high and field observations were insufficient for validating sensor values. Yet error
in either flow sensor—while considered unlikely—was possible.
3.4.2
Spatially Detailed Observations
DTS systems were used in conjunction with heated fiber optic cables to obtain
information on the relative variability of infiltration. Figures 3.9 and 3.10 show the
results of a 1-hour heat pulse taken in November 2008 with about 10 cm of standing
63
water (see Appendix Figure C.10). In brief, substantial variability was not observed
in any of the cable transects spanning the full longitudinal length of the wetland.
Figure 3.9 shows the greatest range of relative variability observed, which differed by
a factor of about two. Various spatial patterns can be observed in the cable transects,
such as the high infiltration feature located at the midpoint of transect NEW and three
distinct rises and drops in infiltration across transect NEW. For the most part, these
features do not necessarily correspond to field observations except on a speculative
level. Figure 3.10 shows the relative variability determined in the southern half of the
wetland. While the average values were similar to the northern half, the greatest
variability observed was well within a factor of two.
Infiltration Rates Calculated with Heat-Pulse - November 2008
50
NWW
NWE
Infiltration (cm/d)
NEW
NEE
40
30
20
0
5
10
15
20
Distance (m)
Figure 3.9 Relative variability of north wetland infiltration based on the thermal
response of heated fiber optic cables. These data were collected in November of
2008 using a 1-hour heat pulse with about 10 cm of standing water in the wetland.
64
Infiltration Rates Calculated with Heat-Pulse - November 2008
50
SWW
SWE
Infiltration (cm/d)
SEW
40
SEE
30
20
0
5
10
Distance (m)
15
20
Figure 3.10 Relative variability of south wetland infiltration based on the thermal
response of heated fiber optic cables. These data were collected in November of
2008 using a 1-hour heat pulse with about 10 cm of standing water in the wetland.
An additional 1-hour heat pulse was performed in June 2009 with about 15 cm of
standing water. Figures 3.11 and 3.12 show the relative infiltrations in the north and
south halves, respectively. The results from these graphs demonstrate that the
average infiltration increased from November, while the variability decreased. It is
suspected that the higher average infiltration is due to greater hydraulic head in the
wetland during the June heat pulse—around 15cm, compared to about 10 cm in June.
The decrease in variability suggests that the development of a soil clogging layer,
changes in clay swelling, or additional settling within the wetland since the fiber optic
installation might have occurred. The greatest range of variability observed from the
June heat pulse ranged from 18 to 27 cm/d—or within a factor of 1.5.
65
Infiltration Rates Calculated with Heat-Pulse - June 2009
50
NWW
NWE
Infiltration (cm/d)
NEW
NEE
40
30
20
0
5
10
15
20
Distance (m)
Figure 3.11 Relative variability of north wetland infiltration based on data collected
in June of 2009 using a 1-hour heat pulse with about 15 cm of standing water.
Infiltration Rates Calculated with Heat-Pulse - June 2009
50
SWW
SWE
Infiltration (cm/d)
SEW
SEE
40
30
20
0
5
10
Distance (m)
15
20
Figure 3.12 Relative variability of north wetland infiltration based on data collected
in June of 2009 using a 1-hour heat pulse with about 15 cm of standing water.
66
3.5
Summary and Conclusions
The objective of this study was to characterize infiltration in the Woodburn WWTP
pilot wetland during the summer and early fall of 2009. Based on a wetland water
budget, Darcy flux infiltration ranged from around 18-28 cm/d when hydraulic head
varied from 33 to 45 cm in late July through mid-September. When hydraulic head
was reduced to 12 cm in late September through early October, infiltration was
observed around 7-9 cm/d. Additionally, infiltration steadily decreased over the
study duration, owing either to soil clogging, instrument error, or another unobserved
process.
Spatial variability in infiltration determined with a DTS and buried fiber optic cables
was not extreme, but within a factor of 2 for all heat pulse observations. Calculations
of November 2008 and June 2009 heat pulses indicate that infiltration rates
determined with identical procedures were comparable, but spatial variability
decreased over that time—potentially due to soil settling, clay swelling or preferential
clogging in zones of higher infiltration. The lack of variability observed in these heat
pulses indicates that underlying drain tiles were not removing substantial quantities of
water. This suggests that the drain tile plugging effort in 2008 was at least
moderately effective.
In considering the use of these results for designing future treatment wetlands at the
site, the wetland designer should be cautious for several reasons. First, the pilot
wetland is relatively small in comparison to full-scale wetland expansion and
heterogeneity in hydrogeology of the surrounding floodplain area could produce
different results. Second, the period of research monitoring was relatively short (less
than 3 months) and did not show infiltration behavior over several years, as would be
occur with long-term treatment operations. Additionally, even in such a short
monitoring period, the wetland exhibited a wide range of infiltration values
depending on the hydraulic head and time of year (since infiltration was decreasing
through the study). Fourth, relative infiltration variability was assessed in an area
67
where drainage tiles had been unearthed and plugged in 2008. Whether the
surrounding area is more or less variable will depend on where the wetland cells are
located and on the effectiveness of underlying drain tiles.
3.6
Acknowledgements
We thank Jason Smesrud at CH2M HILL, the City of Woodburn, and Curtis Stultz,
Jerry Tabler, Mike Arellano, Jordon Garner, and Ramon Garcia at Woodburn’s
Wastewater Treatment Plant.
3.7
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70
4
CONCLUSIONS AND RECOMMENDATIONS
The objectives of this research were to characterize the temperature treatment and
infiltration performance of the Woodburn WWTP pilot wetland. These objectives
were to be achieved using two approaches: through broad, system-wide monitoring
and through spatially detailed DTS observations. Broad observations were conducted
using temperature loggers, flow meters and pressure transducers. Data from these
instruments provided a foundation for understanding the pilot wetland as a whole.
Complementing this understanding, spatially detailed observations were made with
DTS systems using buried and surface-water fiber optic cables. Viewed together,
these datasets provided comprehensive monitoring and led to valuable insights about
the pilot wetland system.
The content of this research was presented in two chapters, representing the two study
objectives. First, chapter 2 discussed the pilot wetland site, methods and results from
the temperature monitoring effort. Second, chapter 3 presented the methods,
calculations and results from the infiltration analysis.
Based on the temperature treatment study, the pilot wetland showed minor effluent
cooling. DTS longitudinal temperature profiles showed that wetland balance
temperature was reached within the first half of the wetland, indicating potential for
additional treatment if inflow temperatures had been warmer. This finding is
supported by inlet and outlet temperature loggers, which showed that reducing the
effluent HRT in September from 2.5 to 0.5 days did not decrease treatment. Had the
pilot wetland been tested against warmer inflows, the degree of temperature reduction
would have been strongly associated with HRT, especially with short HRT times such
as 0.5 days. It is believed that about 4°C effluent cooling occurred in the WWTP
storage lagoon, prior to being treated in the pilot wetland.
71
Longitudinal temperature profiles collected with a DTS over a 3-day study
demonstrated the diel temperature patterns within the wetland. Inflow heat waves
from diel heating cycles in the storage lagoon were quickly absorbed by the wetland
surface water and did not propagate through the wetland system. Middle deep zone
temperatures were consistently cooler than surrounding shallow zones and had less
variance, indicating density-driven stratification of the deep zone for most of the day.
In addition, variances in the heating patterns observed across the longitudinal profiles
suggest that point measurements in the midpoint shallow zones should not be used to
represent temperature treatment through the first (north) half of the weltland.
The infiltration study findings show that system-wide infiltration was a significant
component of the wetland water budget, representing more loss than outflow for most
of the study period. When hydraulic head was decreased from about 40 to 12 cm in
mid-September through early October, outflow accounted for more loss than
infiltration. This may be attributed to a lower hydraulic gradient resulting in less
vertical infiltration, a decrease in lateral bank loss, and lower infiltration rates toward
the end of the study period. The infiltration decline determined in the wetland water
budget had no observed explanation. However, several possibilities were offered,
including soil pore clogging due to organic and sediment accumulation or instrument
error affecting calculations of infiltration in the water budget.
Heat pulses conducted on a subsurface fiber optic cable and collected on DTS
systems were a first-of-its-kind application for wetland research. Interpreting these
datasets with an analytical solution for seepage velocity indicated little relative
infiltration variability in the wetland. The greatest observed variability was in the
north half of the wetland in November, when infiltration varied based on spatial
location by a factor of 2. All other heat pulse data showed relative infiltration
variability was less than a factor of two, and decreased between November 2008 and
June 2009. In addition, the locations of high infiltration were inconsistent between
these dates. It was suggested that post-installation soil settling, or pore clogging in
72
high infiltration zones similar to that mentioned in the system-wide analysis may
explain these observations.
Following the cumulative research findings, several recommendations to those
interpreting these data and points of discussion are outlined below:
First, larger treatment wetlands constructed in different areas of the WWTP site can
be expected to behave differently than the pilot wetland for several reasons. One
reason is that the 0.15 ha pilot wetland had a large perimeter-to-area ratio that
affected its infiltrative capacity. A significant portion of infiltration is believed to
occur through lateral bankloss, which is related to the amount of perimeter area
available. Also, water mounding beneath the wetland is less pronounced if the
wetland has a relatively small area and ample opportunity to propagate infiltration
laterally. Wetlands intended to treat greater volumes of water will need to have
greater areas, which will decrease their perimeter-to-area ratio and result in less
lateral bankloss and more water mounding beneath the center of the wetland areas.
Another reason is that the drain tiles located beneath the wetland were excavated and
plugged to reduce preferential drainage, which might be much larger in other
locations overlying active drain tiles in the floodplain. Finally, if future wetlands are
constructed outside of the floodplain, the underlying soil type and thicknesses will
likely be different, resulting in different hydrogeologic behavior.
Second, these observations were made over a considerably short period of time—less
than three months—and therefore should be viewed within the context of other
comparable studies. If possible, further monitoring of this pilot wetland over
additional operational periods would add insight into these data, as well as into the
pilot wetland performance over longer periods of operation. However, knowledge of
other comparable treatment wetlands—either by geographical location, size, or use—
would certainly add confidence to potential wetland performance and design
decisions going forward.
73
Third, to assess the pilot wetland capacity for temperature reduction it would be
useful to increase the temperature of inflows to values more representative of that
expected. Effluent arriving to the wetland in September was shown to be near to the
wetland balance temperature, therefore little treatment was observed. In addition, no
treatment was observed in the second half of the wetland during the DTS fiber optic
study. By increasing the inflow temperature, the wetland will have greater
opportunity to treat the effluent temperature and this treatment can occur over the
entire length of the wetland.
As previously discussed, Kadlec and Wallace (2008) advised to use water budgets to
determine residuals only with great caution. That same caution is issued here.
Decreases observed in wetland infiltration over the study period may have been
caused by soil clogging processes, another hydrologic phenomenon, or instrument
error in the water budget. If the reported infiltration behavior was accurate,
infiltration in other treatment wetlands on the site may behave differently. These
considerations should be included in determination of water depths, loading rates, and
hydraulic retention times planned for future wetland designs.
74
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78
APPENDICES
79
A
APPENDIX A – AN EXTERNAL CALIBRATION PROCEDURE FOR
DISTRIBUTED TEMPERATURE SENSING DATA
80
A.1
Introduction and Methods
Alterations that are inevitably made to the optical fiber from its handling, installation,
and splice connections require calibrated adjustments to obtain accurate temperature
data. These adjustments are identified as offset, attenuation, and gain. Offset refers
to a positive or negative displacement of the temperature values from their true
values. It is a consistent displacement across an entire stretch of continuous fiber that
is usually due to light loss at a connection. Attenuation refers to loss that occurs as
light travels down the fiber and some of that light escapes by exceeding the refractive
index of the glass core. All fibers have a degree of attenuation and must be
individually calibrated so that temperature values do not lose accuracy with distance.
Finally, gain refers to an inaccuracy in the data that can occur as a function of
temperature. In other words, a DTS installation that has been calibrated at lower
temperatures may lose accuracy at much higher temperatures, or vice versa.
Offset, attenuation, and gain parameters may be accounted for either by userspecified adjustments in the DTS configuration or by external data correction in postanalysis. In the first case, software within the DTS operating system allows the user
to specify adjustments that are then used to internally calculate the corrected values.
The SensorTran DTS 5100 M4 required each of these values to be assigned to
corresponding coefficients for every segment of cable. The Sensornet Oryx required
the user to specify offset and attenuation values for the entire cable, or use a number
of other calibration options such as specifying distances on the cable where
temperatures should be identical, or specifying where temperatures should match an
external PT100 probe. Where convenient, calibration coefficients were assigned in
the DTS configuration to improve data accuracy, but depending on the accuracy
required for the experiment, the user may not want to rely on the DTS calibration for
final results.
81
To determine cable calibrations with greater confidence an external data correction
procedure was developed. This procedure involved using an outside numerical
program to view, organize, and correct the data manually in post-analysis. For this
research, a numerical computer application called MATLAB® (R 2009a) was used.
Once the data was collected, it was imported into MATLAB and manual corrections
were made to calibrate each cable segment.
In addition, critical data collected during DTS operation was necessary to calculate
the offset, attenuation, and gain parameters for calibration. To obtain offset and
attenuation parameters, several meters of cable were coiled and placed in ice-filled
water baths at the beginning and end of each cable segment. Special care was taken
to make sure these baths were a thorough, homogeneous mixture of ice and water
with no temperature stratifications. Offset was calculated as the difference between
the average coil temperature in the ice bath at the beginning of the cable segment and
the actual ice bath temperature as recorded by a high precision thermometer (Figure
A.2). Once determined, this offset value was applied to the entire cable segment
(Figure A.3). Similarly, attenuation was calculated by looking at the average coil
temperatures recorded in both ice baths (at the beginning and end of the cable
segment) and correcting any erroneous slope in the readings with distance. The
attenuation slope was removed by addition or subtraction of the resulting linear error
function (Figure A.4). Although gain was not observed to require significant
correction, it can be adjusted for with simultaneous collection of warm bath and cold
bath data (Figures A.5, A.6 and A.7).
A.2
Results
The results of the calibration effort with plots illustrating corrections to the
temperature profile follow below.
82
Uncalibrated Cable
14
12
Temperature (C)
10
8
6
4
2
0
-2
offset
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.1 An uncalibrated fiber optic cable temperature profile with ice
bath sections on both ends.
Figure A.2 Ice bath temperature collected in the field with a high-precision
thermometer.
83
Cable with Offset Correction
14
12
Temperature (C)
10
8
6
4
2
0
-2
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.3 Offset correction (red) applied to temperature data.
Cable with Attenuation Correction
14
12
Temperature (C)
10
8
6
4
2
0
-2
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.4 Attenuation correction (black) applied to temperature data.
84
Cable without Gain Correction
16
14
Temperature (C)
12
10
8
6
4
2
0
-2
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.5 Temperature data for a cable with an ice bath section (at 120 m)
and a water bath section (at 240 m).
Figure A.6 Water bath temperature collected in the field with a highprecision thermometer.
85
Cable with Gain Correction
16
14
Temperature (C)
12
10
8
6
4
2
0
-2
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.7 Gain correction (green) applied to temperature data.
Calibrated Cable
14
12
Temperature (C)
10
8
6
4
2
0
-2
120
140
160
180
200
220
240
Distance from DTS (m)
Figure A.8 Calibrated cable (green) with offset, attenuation, and gain
corrections.
86
B
APPENDIX B – TEMPERATURE RESULTS OF HEAT-PULSE:
SURFACED PLOTS OF HEATED CABLE SEGMENTS
87
B.1
Explanation of Plots
The following six plots illustrate the 1-hour heat pulses applied to subsurface fiber
optic cable segments. They have been included here to show, in a more visually clear
way, the variability in heating across these segments. The axes consist of
temperature, time, and distance, and the data points have been ―surfaced‖—or
connected by planar shapes—to bring into view the more persistent seepage features.
Figure B.1 can be compared to Figure 3.5 in the text, showing surfaced versus
unsurfaced plots of the same data. Figures B.2 and B.3 are also of the same data,
cable segment ―NEW‖ (see Figure 3.2), but have been rotated to show a high seepage
feature from two different angles. Figure B.4 shows several several ―peaks‖ and
―valleys‖ (corresponding to lower and higher seepage, respectively) in an intriguingly
variable cable dataset. Figures B.5 and B.6 illustrate two other cable segments,
―SEW‖ and ―NWW‖, to provide a greater sense of typical heating data.
All heat pulses shown here are derived from the November, 2008 heat pulse.
88
Heated "NEW" Segment - Profile View
Temperature (C)
25
20
15
10
0
30
60
90
Time (min)
Figure B.1 Surfaced plot of DTS heat pulse data showing ―NEW‖ cable
segment.
Heated "NEW" Segment - Posterior View
Temperature (C)
25
20
15
90
10
0
5
10
Distance (m)
15
20
0
Time (min)
Figure B.2 Variability in heating of ―NEW‖ segment shown across cable
length.
89
Heated "NEW" Segment - Anterior View
Temperature (C)
25
20
15
0
10
20
15
10
Time (min)
90
5
0
Distance (m)
Figure B.3 Variability in heating and cooling of ―NEW‖ segment.
Heated "NWE" Segment - Posterior View
Temperature (C)
25
20
15
10
0
5
10
15
Distance (m)
Figure B.4 Variability in heating of ―NWE‖ segment.
20
0
90
Time (min)
90
Heated "SEW" Segment - Posterior View
Temperature (C)
25
20
15
10
Time (min)
0
5
0
20
15
10
Distance (m)
Figure B.5 Variability in heating of ―SEW‖ segment.
Heated "NWW" Segment - Posterior View
Temperature (C)
25
20
15
10
0
5
10
15
20
Distance (m)
Figure B.6 Variability in heating of ―NWW‖ segment.
0
90
Time (min)
91
C
APPENDIX C – PILOT WETLAND PHOTOGRAPHS: INSTALLATION
AND VEGETATION DISTRIBUTION
92
Figure C.1 Elevated view of the pilot wetland from the south end looking north.
Photo taken 7/28/09.
Figure C.2 Custom designed plow for installing fiber optic cable in wetland soil
at various depths. Sand bags (left) were used to weight the plow base down; the plow
blade (right) with steel tubes used to lay the fiber at four depths—10, 20, 25, 30 cm.
93
Figure C.3 The plow path of a longitudinal transect after cable installation (left)
and an up-close look at the plow path seam before manual compaction (right).
Figure C.4 Two longitudinal transects plowed on the eastern half of the wetland.
94
Figure C.5 Fully-vegetated northern half of the east side of the wetland with middle
deep zone labeled. (taken 9/12/09)
Figure C.6 Hydrocotyle in the western middle area. (taken 9/12/09)
95
Figure C.7 Hydrocotyle partially covering the south deep zone. (taken 9/12/09)
Figure C.8 Eastern (left) and western (right) fully-vegetated northern zones.
(taken 9/12/09)
96
Figure C.9 Eastern half of the wetland looking south from middle deep zone with
digitized locations of the fiber optic transects. Duckweed (green) covers the water.
(taken 09/12/09)
Figure C.10 Pilot wetland conditions during November 2008 heat pulse. (taken
11/11/08)
97
Figure C.11 Algae growth in the west middle zone in early July 2009. (taken 7/8/09)
Figure C.12 Algae growth in the wetland in late July 2009. (taken 7/24/09)