Introduction
Green roof technology has been expanding in recent years. Green roofs provide ecosystem
services in urban areas, including improved storm-water management, better regulation of
building temperatures, reduced urban heat-island effects, and increased urban wildlife
habitat. In order to optimize the performance of such installations, it is necessary to
monitor a green roof and analyze the effects it has to a given building. The two goals of this
project are to: 1) create a site specific green roof optimized for storm water retention, roof
top cooling during summer, and greatly improved roof R value for winter, 2) design and
build an economical and easily transportable instrumentation package that will validate
the above performance criteria for most green roof systems.
Background
Ordinary commercial building roof systems contribute to four specific municipal and/or
building issues: 1) Building storm water run-off directly contributing to the load on
municipal sewage treatment infrastructure, 2) Peak runoff events causing the combined
storm water and sewer runoff to overflow into open urban bodies of water, 3) Dark colored
commercial roof systems generally experience high rooftop temperatures which can
negatively impact building energy consumption, 4) Dark roofing materials also contribute
to the local urban heat island (UHI).
“Green roof” (GR) systems are promoted as an effective method for reducing storm water,
building heat load, and UHI from buildings (Bureau of Environmental Services, 2008).
Additionally green roofs are constructed of more durable/higher quality materials and can
prolong roof longevity two to three times (Penn State, 2006). GR systems have been
modeled and studied for UHI impact, thermal resistance, and water quality (Sailor 2006,
Buccola 2008); all under laboratory conditions. Known disadvantages to a GR over a
traditional roof are the high capital cost associated with installation, need for additional
structural evaluation, and plant maintenance. Green roof systems will become more
attractive to building owners if they can relate higher capital cost to long term savings, in
terms of dollars and cents, over a specified period of time.
Rarely is there a green roof system designed for specific performance objectives, which
makes this test bed unique. Additionally, instrumentation employed to measure GR
performance is generally not installed during GR construction. It is difficult and expensive
to instrument and obtain performance data on previously constructed green roof systems.
Creating a relatively economic and portable instrument package, capable of individually
collecting and normalizing data on a variety of installed green roof systems will allow
designers of green roofs to optimize green roof construction parameters for specific
performance criteria.
A test site has been offered at Sunnyside Environmental School on 3421 SW Salmon. A 96
sqft green roof system has been designed for storm water retention and thermal
performance, see Appendix 4a. An economic and portable instrumentation module has
1|Page
been designed and installed in order to validate performance criteria and provide
modeling/data optimization. Data collected has been used to develop a one-dimensional
representation of heat transfer, R-value, evapo-transpiration, and the reduction in storm
water run-off. In addition to the one-dimensional representation, collected data has
provided an opportunity to model GR performance optimizations.
Mission Statement
The mission of the Green Roof Test Module (GRTM) team is to design and construct a scale
green roof and instrumentation module. The green roof is optimized for the three project
design criteria: 1) 60% reduction in storm water run-off, 2) GR surface temperature no
greater than 10°F over ambient air temperature, 3) Average winter R-value of 13. The test
module is designed for validation of green roof performance criteria, portability, and
durability.
2|Page
Main Design Requirements
Considerations for the design of the green roof test bed and instrumentation module are
based on several criteria, which may be divided into separate criteria for the green roof test
bed and the instrumentation module.
Instrumentation Package – Primary goal of instrumentation is to obtain adequate
measurements of the green roof to verify its design criteria. As a secondary goal the
instrumentation package will be expandable to have the ability to include other
measurements as needed.
Primary instrumentation design objectives:
1. Reduction in cost from current available monitoring solutions (current monitoring
platforms cost in the range of ~$10k-$15k)
2. Be a mobile solution so a system can be setup within an hour and can be moved to
test different locations of the same roof or a different roof altogether.
3. Contain precision components to measure temperature at many locations
simultaneously, water in/out of a tray system, temperature gradient and heat flux
through the system.
Green Roof Test Bed – Considerations for the test bed include water runoff, temperature
difference between roofs (test bed vs. original roof), and insulation values the green roof
may represent.
Primary green roof design objectives:
1. 60% reduction in annual water runoff vs. existing roof.
2. Temperature of the test bed does not reach more than 10°C greater than ambient
temperature.
3. Winter insulation for the test bed of R13 or greater.
Additional design criteria may be referenced in Appendix 5.
Design Alternatives & Selection
The Green Roof Test Bed
To fulfill all three criteria, the green roof must contain a good combination of soil and
plants while maintaining low overall weight. The green roof must contain plants with good
evapo-transpiration and aesthetics. The plants must also be able to grow in a wet or dry
climate. A 60% reduction in water runoff is needed; therefore, soil that is lighter, non-toxic
and has good combination of water retention and drainage was used.
3|Page
CH2MHill has 20psf snow load and 25psf of snowdrift loading that must be accounted for
depending on the section of roof. The certainty of available roof loading in some sections
was unknown; therefore, the system must be light enough and still fulfill the design criteria.
Soil: Two local companies were contacted to get information on soil. An extensive soil with
20 to 30 percent organic material was suggested by Pro-Gro. Tremco, Inc. was contacted,
and suggested use of 80 percent stalite and 20 percent organic soil. However, Pro-Gro was
chosen because data were already collected on Pro-Gro and it was the right choice for our
project
Plants: To gather information about plants in general, Portland Nursery on Stark Street
was visited, and provided information on Yarrow, Sedum, Rye grass, Carex, Vinca and
Heather. Portland Nursery advised against Vinca due to their invasive nature, while Sedum
and Rye grass would work best in a broad range of wet and dry soil conditions, and provide
an aesthetically pleasing mix.
Trays: To find out what trays are being used for the green roof, research was one on the
internet. From the research, it was determined that both steel and plastic trays were being
used depending on the roof load capacity. Don from Columbia Green was contacted to get
more information on plastic trays. Plastic trays were chosen because they are light and
there is no need for a drainage layer.
Drainage Layer: Typical green roof construction includes a drainage layer; however,
Columbia Green plastic tray is designed to eliminate need of drainage layer.
Insulation: Formular® F150 2 inch foam that is commonly available and economical was
suggested by Dr. Sailor. Two inches of insulation under the trays insures a winter R-value
of 10.
Waterproof Membrane: For the waterproof membrane, Dave Myers from Snyder Roofing
was contacted who provided a waterproof membrane.
Test Module
To validate that Green Roof provides 60% reduction in storm water run-off, water entering
and leaving the system has be measured. Water entering and leaving the system can be
measured by either using a combination of Lysimeter, Weather Station and Soil Moisture;
combination of Flow Meter and Weather Station; or combination of Weather Station, Load
Cells and Soil Moisture Sensors.
Weather Station: Four different weather stations were researched; Davis 6162, Davis 6152,
ProWeather Station and the HOBO U30 weather station. All systems will meet our accuracy
needs. Davis 6162 was selected based on accuracy and economics.
Soil Moisture Sensors: Many soil moisture sensors were researched online; however
Decagon soil moisture was chosen due to its accuracy and our past experience with the
sensor. One of the benefits of using Decagon Sensors is they can hook directly to the Davis
weather station.
4|Page
Load Sensors: An online search revealed two load sensors, Futek and Loadstar, which could
meet criteria for a lysimeter. Loadstar sensors are cheaper but Futek load sensors were
chosen due to its accuracy.
To validate that Green Roof surface temperature is no greater than 10°F over ambient air
temperature, the surface temperature of the soil and ambient air temperature has to be
measured. The temperature at the surface of the soil can be measure by using a
thermocouple or by using Infrared Camera. Data from a thermocouple or the Infrared
Camera would then be compared to the ambient temperature readings obtained from the
Weather Station.
Thermocouples: Three different options for thermocouples and thermocouple data loggers
were researched. The Lascar 1-channel logger was chosen because of its integrated logger,
high accuracy, and expandability.
To validate Green Roof provides winter R value of 13, thermocouples were placed at the
soil surface, (beneath rye grass plant canopy), 2cm, 8cm (flux sensor depth) and 10cm
(bottom of soil) below the soil surface. A heat flux sensor was placed at 8cm; see
“Huskeflux Manual”, Appendix 4A. By using 𝑅 = ∆𝑇/𝑞, we could calculate the R-value.
Furthermore, we had to calculate R-value of the GR because it was the only way to measure
its cooling effect during summer months and its insulation properties in winter months.
Heat Flux Sensors: A heat flux sensor is needed to calculate an R-value. Multiple heat flux
sensors were researched online. After looking at different heat flux sensors, the options
were narrowed to Omega (HFS-4) and “Huskeflux” Thermal sensor (HPF01). Huskeflux
sensor was chosen due to its accuracy.
Data Logger: Several options for data logging of load cells, moisture, and flux sensors were
researched. HOBO system 4-channel data logger, Grant 6-channel logger, Campbell PR200
and Lascar 1-channel logger. Campbell data logger was chosen because it has sensor
versatility, large number and variety of channel input options and has a well-understood
interface.
Roof Loading: A structural engineer from WDY was contacted to come verify that the roof
space will hold the approximate load calculated. All calculations were done assuming the
load was 15 psf. However, due to miscommunication, load calculation was done on the
wrong floor. Unfortunately, roof load calculation got delayed for two months delaying
permit acquisition.
City Permit: The permit required to install a green roof on CH2MHill terrace, also requires a
contractor to accept liability, a willing party was not available to accept liability; therefore,
a green roof cannot be installed on CH2MHill terrace. Moreover permitting process takes
more than a month to compete. Therefore, we decided to find an alternative sight to install
a green roof.
5|Page
Selection
The package options that were developed are shown in Table 1.
Package # 1
Package # 2
Package # 3
Package # 4
Package # 5
Weather
Station w/Data
Logger
1
1
1
1
1
Thermocouples
5
5
4
4
4
1
1
1
1
1
3
1
1
0
0
4
4
4
4
4
1
1
6
6
4
1
1
1
1
0
Heat Flux
Sensor
Soil Moisture
Sensor
Load Sensors
Data Logging
Equipment
Summation Box
Table 1: Instrument configurations that will obtain the necessary information to verify the
criteria set for the green roof.
Package # 5 was chosen for sensor accuracy, component integration and budget
constraints. The instrument package consists of a Davis 6152 weather station with console
data logger, a Campbell Scientific CR1000 data logger, two Lascar USB data loggers, a
Decagon soil moisture sensor, a Hukseflux heat flux sensor, four Futek load cells, and four
T-type thermocouples. These sensors and data loggers are placed in a Pelican case for
mobility.
Davis 6152 weather station was chosen for its sensor parameters, accuracy and budget
constraints. T-type thermocouples were chosen because they are suited for measurements
in the −200 to 350 °C range; they are also inexpensive and durable. Decagon EC-5 soil
moisture sensors were chosen because they are durable, have known performance
characteristics and are economical. An additional decision factor Load, flux, temperature
and moisture sensors was ease of integration into the Campbell data logging system.
Hukseflux heat flux sensor was chosen because it’s accurate and has a temperature range of
-30 - +70 °C. Futek load sensors were used to measure the water entering and leaving the
system because it was the most precise way to measure water run-off.
6|Page
Final design
The Green Roof Test Bed
Two varieties of plants were chosen – rye grass and sedum. These plants posses many
similar qualities and were chosen because they are inexpensive, non-invasive, fast growing,
and durable with regard to wet and dry soil conditions. Rye grass and Sedum are ground
cover plants that provide shade (cooling) for the soil and rooftop. Rye grass retains water
well at retaining water in its root system and has a relatively high rate of evapotranspiration as compared to the rates of other plants these two factors along with shading
will be the primary additions to the cooling effect on the overall roof. Rye grass may have
maintenance associated with it though selection of 4” depth of soil will limit Rye grass
growth and possibly reduce maintenance-associated cost. The GRTM has a mix of sedum
species that transpirate diurnally. Sedums have low maintenance and good water
retention & runoff reduction qualities.
“ProGro” soil is an affordable soil that has laboratory R-value data which can be used to
compare with the data collected by the test module.
“Columbia Green” green roof tray system was selected based on soil depth, ease of
installation/removal (at end of 1 year test period), light weight, and water retention
qualities.
A waterproof membrane has been donated to fulfill water protection requirements
between the tray and insulation layers.
2” of Formular F150 insulation was chosen as a base for the green roof system, with a
known R10 insulation value.
*Sub component selection for the primary green roof layers of inorganic and organic
materials was completed, based on the design criteria & decision matrix.
The Test Module
The test module will validate storm water reduction, roof top surface temperature limits
and green roof R-value target.
The Davis 6152 model weather station will provide rainfall and humidity data. Davis soil
moisture sensors will establish the moisture contained within the soil.
The mass balance system (Appendix 4b) will use “Futek” load sensors to determine the
water mass of a 2’x2’ area of green roof and can be extrapolated to the entire green roof
system.
A Decagon soil moisture sensor in conjunction with the mass balance system will be used
to monitor the stored mass of water.
7|Page
The above combination of instruments allows a comprehensible determination of the
water entering and leaving the system, which evaluates the 60% storm water retention
criteria.
The ambient air temperature will be found using the Davis weather station. Lascar data
loggers coupled with T-type thermocouples will be placed at the bottom soil layer, soil
surface and plant canopy. The Huskeflux heat flux sensor will be placed at the bottom of the
soil layer. With the heat flux and temperature measurements the rooftop cooling effect can
be determined and the insulation properties can also be found.
The Davis weather station has a data logger that will acquire rainfall, wind speed, humidity,
and air temperature.
The temperature data from the thermocouples will be recorded using individual Lascar
data loggers.
Futek load sensors will send data input to a third data logger (made by Campbell) and will
be used to record load and heat flux sensor data.
The test module package has potential for sensor additions as well as further
consolidations, see design improvements section.*
Test Module Operation
The internal chronometers of all of the data loggers used in the test module can be
synchronized so the acquired data will have the same time stamp. Data files were imported
into “showWeathertest.m” (MATLAB program, see “GRTM User’s Manual” Appendix 4)
where data reduction and logic statements are applied to compile and evaluate the green
roof performance characteristics.
60% reduction in storm water run-off :The water entering the system due to
precipitation is measured with the use of the rain gauge on the Davis weather station. Data
from the mass balance and moisture sensor provides the change in mass flow over time
due to precipitation storage in and evapo-transpiration from the test plot.
Water mass flow through the systems is measured using the mass balance system (Futek
load cells) and the moisture sensor (Decagon) determines volumetric saturation of the soil.
Each soil type will have an upper saturation (field saturation) where all water coming into
the system is leaving the system through drainage and a slightly lower saturation level
below which water is stored and does not drain. Field saturation for our green roof (the
combination of plants, soil and “Columbia Green” tray system) was 30%. For our green
roof system, drainage stops at and below a saturation level of 29%.
GR surface temperature no greater than 10°C over ambient air temperature:
Temperature differential was determined by measuring ambient temperature (Davis
weather station) and soil surface temperature.
8|Page
Average winter R value of 13:
Insulation R-value is a function of the heat flux which is driven by the boundary condition
temperature differential entering or leaving the system and soil heat storage capacity (a
function of soil mineral properties and moisture content). Soil moisture will vary over time
and therefore R-value will vary over time as well.
The green roof surface has flux exchanges due to solar radiation, convection and evapotranspiration on and from the plants and bare soil. For the purpose of measuring heat flux
through the root/soil cross-section; temperature values for thermal mass storage were
taken at 2cm, 8cm (Huxeflux sensor depth) and 10cm (bottom of plant/soil layer) below the
surface of the soil. The 2cm temperature boundary condition depth will see radiation,
convection, and evapo-transpiration effects that are conducted into the top layer of
plants/soil. The temperature gradient between the boundaries (2, 8 and 10cm) was not
linear but was taken at short time steps that resulted in small differentials (1 – 2 ˚C) and
which we are considering steady state for the purpose of effective R-value calculation.
The R-value of the green roof can be added to the known R-value of the 2” of foam insulation
to achieve the target R-value.
9|Page
Design Evaluation
Green Roof Performance and Test Module Evaluation
60% Stormwater reduction - The system was tested during a 2 week period of heavy
rainfall (2.8” of total rain, 8% of annual rainfall). During this period the overall reduction of
water flowing from the system was calculated to be 54%.
0.7
0.6
inches
0.5
0.4
0.3
Rainfall (in)
0.2
Drainage (in)
0.1
0
5/16 5/17 5/18 5/19 5/20 5/21 5/22 5/23 5/24 5/25
Date
Figure 1: Green roof stormwater reduction for May 16 – May 22, 2010.
The 16 – 26 May testing period had a high amount of rainfall (8% of Portland annual), this
testing period was considered a worst case scenario. The system was designed to provide
a 60% reduction of annual rainfall. The worst case scenario conditions provided a
reduction of 54%. We are confident that the system will provide at least 60% reduction
over an annual period for Portland, OR.
10 | P a g e
Ambient/Green roof temperature difference - Figure 2 indicates peak temperature
differences that meet our criteria of no more than 10 C on 4 of 10 days and as high as 15 C
on 6 of 10 monitored days.
Figure 2: The temperature difference between green roof surface temperature and
ambient air temperature for May 16 – May 26, 2010.
The goal of a maximum temperature difference of 10 C was not fully realized and the
temperature difference instead was 15 C. A possible explanation would be that for a
rooftop mounted system we would expect much higher temperatures on both the standard
rooftop, green roof and the ambient air surrounding the system with rooftop conditions.
Further annual evaluation of temperature differential, at rooftop conditions, are necessary
to understand annual temperature differential impact. This system will be tested on a
rooftop within the next year and this criterion will be reevaluated.
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Effective R-Value - For the 16-26 May test period, an average daily (effective R-value)
insulation value for the soil and plant mass ranged between R 1.8 – 2.6, see Figure 3 below.
Figure 3: Daily effective R-value of the green roof soil and plant mass for May 16 – May 25,
2010.
An R-Value of 3 for the green roof was the target; paired with the R10 foam insulation it
would have created a total R-value of 13. Although no winter data was recorded, this is
where the R-Value of 13 was the priority, the values recorded still fall short of the target.
Reasons for this can be explained by the sparse rye grass, when it has grown thicker it may
provide the extra insulation to reach this goal. Another solution could be an additional 2”
of soil, although the drawback would be the additional weight of the system and a larger
tray would be needed as well.
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Outside of the main criteria the PDS document outlined several other criteria by which to
design for. These can be seen in Table 2 below.
Legal
Building Codes
Weight
Safety
Documentation
Performance
Water
Retention
Water Quality
Temperature
Reduction
Maintenance
Mobility
Targets
Compliant
Less than 15psf
No Leaks
Records for all
Procedures
Met (Yes/No)
Yes
Yes*
N/A
Aesthetics
Marketing
Visual Appeal
Targets
Increase
10
Met (Yes/No)
N/A
Yes
Targets
Within Budget
Less than 1 Hour
to Install
Met (Yes/No)
Yes
5
Yes
Yes
Targets
Met (Yes/No)
60% Annual
Yes*
Reduction
Meets EPA
N/A
Requirements
10°C Above
No*
Ambient Peak CDD
Equal to or Less
than past
maintenance costs
No
Can be moved
without special
equipment
Yes
Instrumentation
Cost
Installation
Compatibility
Resolution
Durability
Adequate for
Meaningful Data
Within -20 to
120°F and able to
withstand impact
loading on the
order of 10lbs
Yes
Yes
Yes
Table 2: Evaluation matrix listing design specifications and overall conclusions on whether
or not the target was reached. N/A, means the target could not be evaluated.
PDS Criteria Evaluation
Most of the criteria for this project have been met with few exceptions, those being Safety,
Water Quality, Maintenance, and Marketing.
Safety regarding leaks is not a parameter that has been tested, it is however the job of the
waterproof membrane to ensure there are no leaks. It has not and cannot be evaluated
being that the green roof was placed on the ground, so this could be a potential change in
the PDS, but seeing as how the green roof should be without leaks whether it be on the roof
or on the ground it has been left in the PDS.
Water quality has not been measured or evaluated. It is assumed that the water coming in
would meet EPA requirements and being that the green roof soil was free of volcanic rock
and is free of heavy metals and other toxic materials that the water runoff would meet
those standards as well.
Maintenance is an issue that was overlooked during the choice of plants, as rye grass does
grow and will need to be cut from time to time. This can be a drawback of using it,
depending on roof access and load characteristics, however the benefits in evapotranspiration and its resiliency were felt to have outweighed the increased maintenance.
13 | P a g e
Marketing was another area that proved to be difficult to measure; hence there will be a
change in PDS regarding any increase in marketing as the goal.
Test Module Comparison
Looking at local green roofs and the ways in which they are monitored there are several
monitoring methods which are most common.
Usually there is some sort of water metering done either via an expensive flow meter
installed in the plumbing or at the top of the roof drain, or there is water collection done
into some sort of container and the water is weighed. The weighing is the cheaper of the
two options but requires considerable labor, while the installation and monitoring of a flow
meter at the drain or in the plumbing can’t be done for less than thousands. Generally
these water metering systems are accompanied by a weather station, or general weather
data is used from the nearest weather station.
The water metering done on the Broadway building uses a $3000 flow meter for each
drain, not including installation costs [Spolek, 6]. BES has water metering services where
they install and monitor stormwater runoff for approx. $7,400/year per meter to rent
equipment and have data taken [BES, 3].
The benefit of this test module is that it requires minimal labor, once properly setup; is
relatively inexpensive in the long run, and is a mobile system and therefore can be moved
to other test sites with ease. The total cost of the system is a onetime cost of $5100, and is
much more than just a water monitoring system.
Test Module Future Considerations
The addition of a Campbell AM16/32 B Multiplexer would allow the inclusion of an
anemometer, rain gauge, pyronometer, thermocouples, and options of expandability. The
above option removes the need for the Davis weather station and Lascar dataloggers;
simplifying the logging and data download. This also reduces the overall cost of the system.
Such an approach was not foreseen during the development of the test module but would
be a preferable option.
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Conclusion
Overall the project has been a resounding success. Based on the 10-day test period the
green roof performance criterion have not been fully realized, although the results are very
promising for an annual analysis. Instrumentation performance has met expectations, but
can be improved by consolidating and expanding its capabilities for a price comparable to
the current version.
Acknowledgements
Special thanks to CH2MHill for providing an opportunity and budget to work on this
project, Oregon Pacific Development Company for their donation as well, Pro-Gro for
donating soil, Columbia Green for donating trays, and Snyder Roofing for donating
waterproof membrane.
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References
1. Columbia Green Technologies, Inc. The New Standard in Eco-roof Technology. 2010.
<http://www.columbiagreenroof.com/home>.
2. Penn State Center for Green Roof Research. "Penn State Green Roof Research: About Green
Roofs." Department of Horticulture. Pennsylvania State University, 25 July 2006. Web. 06
June 2010. <http://horticulture.psu.edu/cms/greenroofcenter/history.html>.
3. Bureau of Environmental Services. 2008 Stormwater Management Facility Monitoring
Report. City of Portland, OR. Dec 2008. 23 Jan 2010. pp. 1-2
<http://www.portlandonline.com/bes/index.cfm?c=36055&a=232644>.
4. David Sailor. “The Urban Heat Island Mitigation Impact Screening Tool (MIST).
Environmental Modeling & Software, Vol 22, Issue 10, p. 1529-1541, October 2007.
5. Norman Buccola. “A laboratory Comparison of Green-Roof Runoff”. Environmental
Engineering 6. Master’s Thesis, Portland State University, Portland OR. July 2008.
6. Spolek, Graig. "Broadway and Multnomah County Green Roof." Personal interview. 2 June
2010.
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Appendices
Appendix – 1A
Decision Matrix for Green Roof
Non-organic
Plants
Metal tray Metal tray w/
Soil
Plastic
Vincas
Rye grass &
Phillips Pro-Gro
w/aggregate
geocomp
w/ absorb
& Rye grass
Sedum
Cost
4
2
3
3
3
2
4
Applicability
2
2
3
2
4
3
4
Aesthetics
-
-
-
2
4
-
-
Durability
3
3
2
4
5
-
-
Weight
1
1
4
-
-
-
-
Total
10
10
12
11
16
5
8
Table 1a: To decide on the most appropriate option for Green Roof, we made a matrix which looked at cost,
applicability, aesthetics, durability and weight. On a scale from 1 to 5, 5 being the best, we compared all of the
criteria and selected the one with the highest total.
Appendix -1B
Decision Matrix for Test Module Sensors
60% water reduction
Flow Meter &
Precip, Soil
Utility data
Moisture &
Temp > 10°C ambient
Lysimeter
IR camera
Ambient/
R-Value >13
Temp &
Temp &
Surface temp GERTY
Heat flux
Mass
Cost
5
3
2
1
4
5
3
Applicability
1
4
4
4
3
2
4
Ease of Use
2
3
3
2
4
2
4
Durability
-
-
-
2
4
4
4
Total
8
10
9
9
15
13
15
Table 1b: To decide on the most appropriate test instrumentation using the design criteria we made a matrix
which looked at cost, applicability, ease of use, and durability. On a scale from 1 to 5, 5 being the best, we
compared all of the criteria and selected the one with the highest total.
17 | P a g e
Appendix -1C
Decision Matrix for Test Module Package
Cost
Precision
Power requirements
Sensor Integration
Durability
Total
Package #1
Package #2
Package #3
Package #4
5
1
1
4
4
4
4
4
4
4
3
4
5
3?
4
3
4
16
17
19
19 ?
4
1
5
indicates an unknown parameter which is currently being investigated.
Table 1c: To decide on the most appropriate test instrumentation package using the design criteria we made a
matrix which looked at cost, precision, power requirements, ease of use, and durability. On a scale from 1 to 5,
5 being the best, we compared all of the criteria and selected the one with the highest total.
18 | P a g e
Appendix -2A
Green Roof Material Specification Sheets
Columbia Green tray specifications:
2.4
TRAYS
1. Performance / Design Criteria: Engineer to:
2. Retain, Detain and meter rain and drip irrigation water.
3. Allow hydration of plants and prevent root rot.
4. Allow phytoremediation (removal of contaminates) from soil and water at bottom of trays.
5. De-energize wind flow under trays reducing chance of wind uplift.
6. Eliminate need for additional drainage material, root barriers, and filter fabric.
7. Tray Size: 2 foot square 4-5/8 inch deep.
8. Material: 100 percent post-industrial recycled content, injection molded,100 mil polypropylene.
9. Water-Detention Ridges and Troughs: Eleven 3/4 inch wide by 5/8 inch high troughs and
corresponding troughs
10. Molded Drain Holes: 1/8 inch diameter. Nine holes located at tops of water-retention ridges and
one at each trough.
11. Interlocks: Two flat and two overlapping top edges designed to connect and hold adjacent trays
together fully encapsulating the roof.
12. Sides: Sloped at 5 degree angle from top to bottom allowing adequate airflow mitagaing the
posibility of mold.
13. Clearance: 5/8 inch above underlying roof membrane to allow water to flow freely under and
around trays.
14. Connection Holes and Fasteners:
15. Four 3/8 inch holes, aligned and centered in each vertical side panel.
16. Quick-lock fasteners.
17. Hook and quick-lock fastener for 8 p.s.i. xeriscaping drip irrigation system.
18. Weight:
19. Unloaded Tray Weight: 3.6 pounds.
20. Loaded With Mature Plants and Fully Saturated 23 to 26 pounds per square foot,
21. Moisture Content Weight: 18 to 20 pounds per square foot, fully saturated.
22. Color/Sheen: Black/semi-gloss.
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Insulation layer specifications:
20 | P a g e
T-type thermocouple wire specifications:
Pro_gro extensive soil specifications:
Extensive – Also referred to as eco-roofs, and low-profile – They have thinner and less numbers of
layers, so therefore they are lighter, less expensive and very low maintenance. Extensive green roofs
are built when the primary desire is for an ecological roof cover with limited human access. The
minimum growing media or soil substrate starts at about 2 1/2” to 6” at most (although vegetative mats
can actually have even less than 1" of growth media); the engineered soil media contains 70 – 80%
inorganic or mineral material (or higher) to 20 – 30% organic (or less). Low growing, horizontally
spreading root ground covers with general maximum plant heights of 16 – 24” are ideal. Alpine-type
plants are successful because they are high drought, wind, frost, and heat tolerant, all necessary
attributes for green roofs. Plants include sedums and other succulents, flowering herbs, and certain
grasses and mosses. Fully saturated weights range from a low of about 10 – 50 lbs/sq. ft.
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Davis weather station data logger specifications:
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Lascar thermocouple data logger specifications:
Measurement Range
K-Type Thermocouple: -200°C to 1300°C
J-Type Thermocouple: -130°C to 900°C
T-Type Thermocouple: -200°C to 350°C
Thermocouple Probe
(Included)
Type: 4" Stainless Steel K-Type
Range: 0°C to 400°C (32°F to 752°F)
Yellow Type K Connector
Part #: EL-TC-K4-15
Resolution
1.0°C (2.0°F)
Accuracy
±1.0°C (±2.0°F) @ -10°C to 40°C (14°F to 104°F)
Data Storage Capacity
32,000 Samples
Sampling Rate
1 Second to 12 Hours
Operating Range
Temperature: -10°C to 40°C (14°F to 104°F)
(Note: Logger Should Not be Subjected to Temperatures Outside Operating
Range)
Battery
User Replaceable 1/2AA 3.6V Lithium
Battery Life
Typically 6 Months (Dependant on Sampling Rate and Environment)
Software
Windows 2000, XP and Vista (32-bit) Compatible
LED
Green: Recording and Logging
Red: Alarm Thresholds Met
Orange: Low Battery or Logger Data Capacity full
Alarm
Visual - Blinking Red LED
Standards
Compliance
RoHS
Dimensions
118mm Length x 27mm Width
23 | P a g e
Appendix -3A
Water Mass Balance (WMB)
The WMB is a precision mass sensing device that will allow continuous monitoring of GR mass changes as a
result of water moving through a characteristic green roof element. For our project the characteristic element
that will be focus for mass balance monitoring will be a single 2’x2’x4” “Columbia Green” tray. The tray selected
for monitoring will be situated such that edge effects of the 96𝑓𝑡 2 GR will be negligible. A large part of our
teams approach to cooling the roof is through choice good soil evaporative and plant transpiration qualities
(evapT).
Given: The design criteria for storm water retention and rooftop cooling require an understanding of the
relationship between mass flow of water in and out of the GR. Water mass inputs to the GR come from
precipitation and irrigation. The water mass outputs come from mass drained from the tray, mass
evaporated from the soil and the mass transpired from the plants. Additionally a portion of water mass is
stored within the soil/plant system.
Note:
1. Direct monitoring of roof top down spouts would seem to be the easiest method for collection of bulk
water mass outputs. At this time it is a great expense and time intensive to design construct and get city
approval for direct, continuous monitoring of roof top down spouts.
2. Soil compaction will change saturation level at which water mass drainage begins.
Find: a, b, and c are primary questions to answer. Secondarily d, e, f and g are of interest and will be
answerable with solutions from relationships in a, b and c, and data collected from the GRTM.
a. Mass drained from the WMB element?
b. Mass evapo-transpired from soil/plants in the WMB element?
c. Mass stored within the element is measured by the WMB or moisture sensors as percent volumetric
water content (𝜽) and must be converted to 𝒎𝒔𝒕𝒐𝒓𝒆𝒅 .
d. At what level of saturation does soil begin to drain?
e. How does drainage occur as a function of saturation?
f.
What does this curve look like?
g. Does the saturation vs. drainage curve reach a location where mass in = mass drained?
24 | P a g e
Solution:
Assumptions:
1. Water mass drainage only occurs at a specific level of soil saturation.
2. When soil/plants are fully saturated and Relative Humidity is over (95% ?):
a. Mass out due to evapotranspiration will be at a negligible value, 𝐦𝐞𝐯𝐚𝐩𝐓 ≫ 𝟎.
b. Mass out is due to 𝐦𝐝𝐫𝐚𝐢𝐧𝐞𝐝 ≅ 𝐦𝐩𝐫𝐞𝐜𝐢𝐩 + 𝐦𝐢𝐫𝐫𝐠 ,
c.
𝐦𝐢𝐫𝐫𝐠 @ 𝐬𝐚𝐭𝐮𝐫𝐚𝐭𝐢𝐨𝐧 𝐬𝐡𝐨𝐮𝐥𝐝 = 𝟎
∴ 𝐦𝐝𝐫𝐚𝐢𝐧𝐞𝐝 ≅ 𝐦𝐩𝐫𝐞𝐜𝐢𝐩
3. When soil/plants are not fully saturated 𝐦𝐢𝐧 will go to 𝐦𝐬𝐭𝐨𝐫𝐞𝐝 until saturation is reached.
Where
𝑬𝒒(𝟏): min = mout
𝑬𝒒(𝟐): min = mprecip + mirrg
𝑬𝒒(𝟑): mout = mevapT + mdrained
∴ 𝑬𝒒(𝟏 𝒕𝒐 𝟑)
𝑔𝑖𝑣𝑒𝑠
𝑬𝒒(𝟒): = mprecip + mirrg = mevapT + mdrained − mstored
𝐦𝐩𝐫𝐞𝐜𝐢𝐩 = (∀precip ∗ ρwater ) = (Davis weather station Precip gauge output ∗ ρwater )
𝐦𝐢𝐫𝐫𝐠 = (∀irrg ∗ ρwater ) = (Manual Irrigation Log ∗ ρwater )
At saturation 𝑬𝒒(𝟒) becomes 𝑬𝒒(𝟒𝒂) = 𝐦𝐩𝐫𝐞𝐜𝐢𝐩 = (∀irrg ∗ ρwater ) = 𝐦𝐝𝐫𝐚𝐢𝐧𝐞𝐝
At less than full saturation 𝑬𝒒(𝟐) 𝐛𝐞𝐜𝐨𝐦𝐞𝐬 𝑬𝒒(𝟐𝒂) 𝐦𝐢𝐧 = 𝒎𝒔𝒕𝒐𝒓𝒆𝒅 .
Evapotranspiration comes from the water mass stored in the soil and is the change in elemental stored
water mass over time.
𝐦𝐞𝐯𝐚𝐩𝐓 = 𝒎𝒔 (𝒊+𝟏) − 𝒎𝒔(𝒊) = ∆𝒎𝒕𝒓𝒂𝒚 (𝑾𝑴𝑩)
25 | P a g e
Appendix -3B
R-Value
Given: R-value across the entire thickness of green roof, from surface plant mass to water proof membrane
layer, can be calculated using the equation 𝑹𝒕𝒐𝒕𝒂𝒍 =
𝑻𝟏 −𝑻𝟓
,
𝒒𝒇𝒍𝒖𝒙
where 𝐑 𝐭𝐨𝐭𝐚𝐥 = 𝐑 𝐩𝐥𝐚𝐧𝐭𝐬 + 𝐑 𝐬𝐨𝐢𝐥 + 𝐑 𝐭𝐫𝐚𝐲/𝐦𝐞𝐦 + 𝐑 𝐢𝐧𝐬𝐮𝐥𝐚𝐭𝐢𝐨𝐧.
𝐑 𝐢𝐧𝐬𝐮𝐥𝐚𝐭𝐢𝐨𝐧 = 𝐾𝑛𝑜𝑤𝑛
Find:
h. In-situ 𝒒𝒇𝒍𝒖𝒙.
i.
R-values for plants and soil. Values will change with changes to temperature and soil moisture boundary
conditions for each of these layers.
j.
R-value for in-situ tray/membrane assembly
Solution:
a. Flux measured (fig 1) at the bottom of the soil layer  𝒒𝒇𝒍𝒖𝒙 = 𝐪𝐟𝐥𝐮𝐱 𝐬𝐞𝐧𝐬𝐨𝐫 .
b. Flux across the system will change only with a change in R and T. Knowing the flux from part (a) and
temperature values collected from T1 , T2 , T3 & T4 (fig 1) will determine R-value across the plant and soil
layers through the following equations:
𝐑 𝐩𝐥𝐚𝐧𝐭𝐬 =
𝐑 𝐬𝐨𝐢𝐥 =
𝐓𝟐 − 𝐓𝟏
𝐪𝐟𝐥𝐮𝐱 𝐬𝐞𝐧𝐬𝐨𝐫
𝐓𝟑 − 𝐓𝟐
𝐪𝐟𝐥𝐮𝐱 𝐬𝐞𝐧𝐬𝐨𝐫
c. Our system will not have a drainage layer so knowing the flux from part (a) and temperature values
collected at T3 & T5 (fig 1) will determine R-value for the tray/membrane system.
𝐑 𝐭𝐫𝐚𝐲/𝐦𝐞𝐦 =
𝐓𝟓 − 𝐓𝟑
𝐪𝐟𝐥𝐮𝐱 𝐬𝐞𝐧𝐬𝐨𝐫
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Figure 1: Heat Transfer Diagram
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Appendix 4:
Green Roof Test module
unit users’ manual
28 | P a g e
Table of Contents:
Introduction to the system

Purpose of system …………………………………………………………………………………………………………………4

What information you can get from the system ………………………………………………………………….…4
Components and hardware documentation

Davis weather station…………………………………………………………………………………………………………….4

Campbell data logger……………………………………………………………………………………………………………..5

Futek load sensor……………………………………………………………………………………………………………………5

Huskeflux heat flux sensor……………………………………………………………………………………………………..5

Decagon moisture sensor……………………………………………………………………………………………………….6

Thermocouples……………………………………………………………………………………………………………………….6
Assembly of the test module (preparation of the unit, cabling)

Assemble the weather station………………………………………………..……………………………………………..6

Assemble the Campbell measurement & control system……………………………….…………….………..9

Assemble the test tray……………………………………………………………………………………………………………11
Installation Instructions

Installation of the test tray into the green roof……………………………………………………………………..13

Install the weather station/ data logger.………………………………………………………………………………..16
Data collection and reduction

Collecting test data from the weather station unit……………………………………………………………....16

Collecting test data from the Campbell data logger………………………………………………………………16

Collecting data from the Lascar USB data loggers………………………………………………………………..17
Portability

Proper storage of the test module equipment……………………………………………………………………..17

Disassembly of the test tray………………………………………………………………………………………………….18
Maintenance & Troubleshooting

Davis weather station………………………………………………………………………………………………………….….18

Campbell data logger…………………………………………………………………………………………………………..…21
29 | P a g e

Futek load sensor………………………………………………………………………………………………………………..….21

Huskeflux heat flux sensor…………………………………………………………………………………………………..…21

Decagon moisture sensor……………………………………………………………………………………………………....21

Thermocouples…………………………………………………………………………………………………………………….…21
Appendix

A. Additional equipment specifications……………………………………………………………………………………22

B. Additional equipment setup information (calibrations)……………………………………………………….29

C. Sample data…………………………………………………………………………………………………………………………31

D. Additional code……………………………………………………………………………………………………………………33
30 | P a g e
Introduction to the system
Purpose of the green roof test module:
The purpose the green roof test module is to measure the thermal resistance (R-value) of the
green roof system, monitor the temperature difference throughout the system, and to track the water
runoff from the system.
What information you can get from the system:
The system will give the ambient temperature, the amount of precipitation, humidity, wind
speed and direction from the weather station. The load sensor platform keeps track of changes in the
mass of the test tray, which will be primarily due to water run-off out of the system. As a secondary
check, a moisture sensor is used to keep track of the quantity of water within the soil. The temperature,
mass change and soil moisture are used to calculate the storm water run-off of the system. There are 3
additional temperature sensors in the system which will monitor the change in temperature throughout
the soil. The thermocouple will be used to verify the difference in surface temperature to ambient. A
heat flux sensor is placed in the test tray (buried in the soil) which will monitor the heat flux through the
soil. The temperature difference through the soil and the measured flux will be used to calculate an
estimated value of R-value for the system.
Components and hardware documentation
Davis weather station:
Wireless Vantage Pro2™ (Model 6152)
The console may be powered by batteries or by the included AC‐power adapter. The wireless ISS is solar
powered with a battery backup. Use WeatherLink™ for Vantage Pro to let your weather station
interface with a computer, to log weather data, and to upload weather information to the internet. The
6152 relies on passive shielding to reduce solar‐radiation induced temperature errors in the outside
temperature sensor readings. The weather station has its own console and records data in internal
memory until it is removed with the software. See page 16 for instructions to use the provided
software.
31 | P a g e
Campbell data logger:
CR1000 Measurement and control system
The module measures sensors, drives direct communications and telecommunications, reduces data,
controls external devices, and stores data and programs in on-board, non-volatile storage. The
electronics are RF shielded and glitch protected by the sealed, stainless steel canister. A battery-backed
clock assures accurate timekeeping. The module can simultaneously provide measurement and
communication functions. The CR1000 has 2 MB of flash memory for the Operating System, and 4 MB
of battery-backed SRAM for CPU usage, program storage, and data storage. Data is stored in a table
format. The storage capacity of the CR1000 can be increased by using a Compact Flash card. The
CR1000 has 8 channels which are used with the load sensors, the heat flux sensor, and the moisture
sensor.
Futek load sensors:
Model LLB350
The standard LLB350 Miniature Load Button model has a 1.0” outside diameter and a 10 feet long 29
AWG 4 conductor shielded Teflon cable. The Miniature Load Button offers high accuracy. It has
Nonlinearity of ±0.5% and Deflection of 0.003” nominal. There are 4 load sensors which are set into a
loading platform. The load sensors are connected to the CR1000 and monitored through the LoggerNet
program. See Table 1 on page 10 for specific channel connections.
Huskeflux heat flux sensor:
Model HPF01
The HPF01 serves the measure the heat flux flow through the object in which it is incorporated or
mounted upon. The sensor employs a passive thermopile detector (no power is required), which
generates a millivolt output signal resulting from the differential temperature across the ceramic plastic
body of the HPF01 and proportionate to the local heat flux. Determining heat flux with this sensor
requires a connection to either a data logger or digital voltmeter with a measurement resolution of 25
µV or better. To find the heat flux in units of 𝑊/𝑚2 , simply divide the HPF01 millivolt output signal by
the factory supplied calibration factor. The heat flux sensor is monitored through the LoggerNet
program and connected to the CR1000 data logger. See Table 1 on page 10 for specific channel
connections.
32 | P a g e
Decagon moisture sensor:
Model EC-5
The EC-5 obtains volumetric water content by measuring the dielectric constant of the media through
the utilization of capacitance/frequency domain technology. In addition, the EC-5 sensors incorporate a
high frequency oscillation, which allows the sensor to accurately measure soil moisture in any soil or
soilless media with minimal salinity and textural effects. Factory calibrations are included for mineral
soils, potting soils, rock wool, and perlite. The moisture sensor is connected into the CR1000 data logger
and placed in the soil approximately 2 inches from the bottom of the tray and centered in the tray. The
monitoring for the moisture sensor is done with the LoggerNet program. See Table 1 on page 10 for
specific channel connections.
Thermocouples:
The Type T thermocouples are suited for measurements in the −200 to 350 °C range. Since both
conductors are non-magnetic, there is no abrupt change in characteristics. Type T thermocouples have a
sensitivity of approximately 43 µV/°C. The thermocouples are wired into the Lascar USB data logger s
and monitored with the program provided.
Assembly of the test module (preparation of the unit, cabling)
Assembly of the Davis weather station:
Step 1: Assemble the Anemometer
The anemometer measures wind direction and speed. The anemometer arm requires assembly before
it can be attached to the rest of the ISS unit. Locate the following parts to complete this assembly.
 Anemometer arm
 Anemometer base
 Drip ring
 Allen wrench (0.05”)
 #4 machine screw, #4 tooth-lock washer, #4 hex nut
Attaching the anemometer arm to the base: (See Figure 1 for part reference)
1.
2.
3.
4.
Insert the anemometer arm into the base, sliding the cable through the notch in the base.
Line up the small hole in the arm with the holes in the base.
Insert the machine screw through the holes in the base and arm.
Slide the tooth-lock washer and nut onto the machine screw and secure the screw with a Philips
head screwdriver.
33 | P a g e
5. Press the sensor cable firmly into the channel in the base, starting from the arm until the
bottom of the base is reached.
Figure 1: Anemometer assembly. *See footnote1
Step 2: Attach the wind cups
1. Push the wind cups up onto the anemometer’s stainless steel shaft, sliding the cups up the shaft
as far as possible. If the cups are not pushed up as far as possible, the anemometer will function
improperly. See Figure 2.
2. Use the Allen wrench provided to tighten the set screw on the side of the wind cups. The wind
cups should drop slightly when you let go. Ensure the set screw is very tight.
3. Spin the wind cups to verify they spin freely. If the wind cups don’t spin freely, take them off
and repeat the installation process.
1
This picture is courtesy of Davis Instruments; www.davisnet.com
34 | P a g e
Figure 2: Attaching the wind cups to the anemometer. *See footnote2*
Step 3: Orientation of the wind vane
The wind vane rotates 360° to display current and dominant wind directions on the compass rose of the
console display. To obtain accurate readings, the vane must be correctly oriented when mounting the
anemometer outside. By default, the wind vane reports the correct wind direction if the anemometer
arm points true north. To ensure correct orientation of the wind vane, mount the anemometer so that
the arm points true north. The wind vane will be ready for use immediately.
If your anemometer arm cannot be mounted aiming true north, you will need to calibrate the wind
direction on your console to display accurate wind directions. See Appendix B for instructions on the
calibration.
2
This picture is courtesy of Davis Instruments; www.davisnet.com
35 | P a g e
Assembly of the Campbell data logger:
Step 1: Assemble the data logger
Figure 3: Campbell data logger CR1000. *See footnote3
1. There are 8 differential channels which measure voltage or temperature levels. Connect all of
the sensors to the CR1000. Attach the moisture sensor to the first output terminal. Attach the
heat flux sensor to the second output terminal. Attach the thermocouples to the third and
fourth output terminals. Attach the four load sensors to the remaining terminals. See Table 1
for more details.
3
This picture is courtesy of Campbell Scientific; www.campbellsci.com
36 | P a g e
Diff
SE
Diff
SE
Channel Channel Sensor
Wire Color Channel Channel
1
1
Moisture
Red
5
9
1
2
5
10
ground
ground
2
3
Flux
White
6
11
2
4
Flux
Green
6
12
ground
Black/Shield
ground
3
5
TC(1)
Blue
7
13
3
6
TC(1)
Red
7
14
ground
ground
4
7
TC(2)
Blue
8
15
4
8
TC(2)
Red
8
16
ground
ground
VX1
Moisture
White
VX2
Sensor
LC(1)
LC(1)
LC(2)
LC(2)
LC(3)
LC(3)
LC(4)
LC(4)
LC(1-4)
Wire Color
Green
White
Black/Shield
Green
White
Black/Shield
Green
White
Black/Shield
Green
White
Black/Shield
Red
Table 1: CR1000 channel wiring connections.
2. Power should be connected to the CR1000 unit. Any 12 V dc source can power the CR1000; a
PS100 or BPALK is typically used. The PS100 provides a 7- A hr sealed rechargeable battery that
should be connected to a charging source (either a wall charger solar panel). The BPALK
consists of eight non-rechargeable D-cell alkaline batteries with a 7.5-Ahr rating at 20°C. Also
available are the BP12 and BP24 battery packs, which provide nominal ratings of 12 and 24 A
hrs, respectively. These batteries should be connected to a regulated charging source (e.g., a
CH100 connected to an unregulated solar panel or wall charger). The output data file will give
a battery life update. The battery will need to be monitored to ensure it is above ~7V or the
unit will stop functioning.
3. The RS-232 connection is used with a converter to USB and the USB is then connected to a
laptop that can run the LoggerNet program. See Figure 4.
Figure 4: Converter for CR1000 from RS232 to USB to the computer.
37 | P a g e
Assembly of the test tray:
1. Install heat flux sensor in the center of the tray. See Figure 5 for sample placement of sensor.
2. Install soil which was removed from the green roof until the tray is approximately half full. Add
the moisture sensor. See Figure 6 for actual horizontal placement of sensors.
3. Install the additional soil to fill the tray. A thermocouple should be added to the tray to
measure the soil temperature 2 cm below the surface of the soil. An additional thermocouple
will be set on the surface of the soil. Figure 7 has a final assembly expanded view of the tray.
Figure 5: Sample placement for the heat flux sensor. *See footnote 4
4
This picture is courtesy of Campbell Scientific; www.campbellsci.com
38 | P a g e
Figure 6: Horizontal view of test tray with instrumentation.
Figure 7: Assembly of the test tray.
39 | P a g e
Installation Instructions
Installation of the test tray:
1. Install the load sensor platform in the ground or surrounded by trays, depending on the setup.
Lower the tray in to place on the platform. It is critical that the tray is set on the platform so
that only the tray is being weighed. Figure 11 shows how the platforms are setup.
2. Connect all of the sensors to the weather station and the data logger through the side of the
equipment case (Figure 12).
Figure 11: Load platform setup.
40 | P a g e
Figure 12: Side entrance for wiring into the equipment case.
Davis weather station:
Install anemometer
1. While holding the mounting base against the pole, place a U-bolt around the pole and
through the two holes in the base.
2. Place a flat washer, a lock washer and a hex nut on each of the bolt ends.
3. Swivel the anemometer until the arm is pointing north (See Figure 13).
Note: If your anemometer arm cannot be mounted aiming true north, you will need to calibrate the
wind direction on your console to display accurate wind directions (See Appendix B).
Figure 13: Installation of the anemometer to the top of the pole.
41 | P a g e
Install weather station
1. After connecting all of the pieces of pole, mount the pole to the side of the equipment case.
Figure 14 shows the case.
Figure 14: Securing the pole to the equipment case.
2. Mount the weather station on the pole with a U-bolt low near the top of the equipment case.
Make sure the weather station is high enough up the pole that the case can open freely. Shown
in Figure 15.
Figure 15: Mounting of the weather station to the pole with a U-bolt.
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Install the Vantage Pro 2 terminal
The Vantage Pro 2 terminal will need to be kept out of direct sunlight and kept dry so it is best to leave
the unit in the equipment case after the data is collected out of the memory.
Campbell data logger:
The CR1000 will need to remain in the equipment case during logging to protect it from moisture.
Data collection and reduction
Davis weather station:
The weather station program used for data logging collects data on assigned intervals (1 min
recommended). Additional code (in Matlab) collects the data from each port and stores it so that a text
or excel file can be used to analyze the data. The standard configuration will output a file similar to the
table shown in Appendix C. Most of the data taken by the weather station is not used in the calculations
done on the system, but may be useful for tracking additional parameters.
To collect data from the weather station:
1. Open the Davis weather station software.
2. Click on the “Get collected data” icon on the top toolbar (second icon from the right). A notice
will pop up saying the data is being downloaded.
3. Once the data is downloaded, click on the “Browse” icon on the top toolbar (fifth icon from the
right).
4. Select “Export data” from the Browse menu.
5. Once the data is transferred to the computer, the data logger memory is cleared.
Campbell data logger:
LoggerNet is Campbell Scientifics full-featured data logger support soft ware. It is referred to as “fullfeatured” because it provides a way to accomplish almost all the tasks you’ll need to complete when
using a data logger. LoggerNet supports combined communication options (e.g., phone-to-RF) and
scheduled data collection. Additional code (in Matlab) collects the data from each port and stores it so
that a text or excel file can be used to analyze the data. The standard configuration will output a file
similar to the table shown in Appendix C.
To collect data from the CR1000:
1. Open the LoggerNet program.
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2. Select “Connect” from the toolbar that appears.
3. In the box that appears, make sure the status on the bottom left of the box says “Disconnect”
(which shows that you are connected to the logger).
4. Select “View data” and a file will open which shows all of the data collected.
5. Click on the “text format” icon on the top toolbar (second icon from the right). Another window
will open. The data from this window will need to be copied and pasted into a text file (using
Notepad is suggested).
6. Once the data has been saved, close data window and click on the “Disconnect” button on the
bottom left of the window. This will close the connection to the data logger and the software
can then be closed.
Lascar USB thermal data logger:
To collect temperature data from the Lascar logger:
1. Attach the USB end of the logger to the computer USB.
2. Open the Lascar USB data program program.
3. Select “Get data”. The data will be saved in a text file.
Portability
Proper storage of the test module equipment:
The equipment will need to be placed into the black equipment case.
1. Remove the weather station from the post it is secured on. Remove the anemometer arm and
wind cups.
2. Take down the anemometer and weather vane from the post.
3. Remove the U-bolts from the equipment case that hold the post in place and take the post
apart.
4. Place the weather station in the equipment case after verifying the rain collector is empty and
folding the antenna down. The weather station should be put in the largest foam cutout on the
upper left as you look in the case.
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5. The CR1000 will remain in the foam cutout in the lower right quadrant. The battery connection
and DB 9 connector (RS232) should be disconnected from the CR1000.
6. The Davis terminal (Vantage Pro 2) should be turned off and the antenna lowered to the side of
the unit. The terminal will fit into the foam cutout in the lower left side of the equipment case.
7. The cables leading out of the equipment case will need to be brought into the case by loosening
the connector and pulling the wires back into the case.
Disassembly of the test tray:
1. The test tray will need to be lifted out of the ground so the load sensor platform can be
removed.
2. Remove the plant layer from the test tray and remove the temperature, moisture and heat flux
sensors from the tray of dirt. The dirt can be placed back in the hole the tray was occupying and
the plant layer should be place back over the dirt.
Maintenance & Troubleshooting
Davis weather station:
If a Sensor Functions Intermittently
Carefully check all connections from the sensor to the ISS. Loose connections account for a large portion
of potential problems. Connections should be firmly seated in receptacles and plugged in straight. To
check for a faulty connection, try jiggling the cable while looking at the display. If a reading displays
intermittently on the console as the cable is jiggled, the connection is faulty. Try removing and then reinstalling the cable to correct the faulty connection. If the sensor still functions intermittently, contact
technical support at Davis Instruments.
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5
Most Common Rain Collector Problem
If the rain collector seems to be under-reporting rainfall, remove the rain collector cone to clean the
tipping bucket and clear out any debris. Make sure the cable tie around the tipping bucket has been cut
and removed.
Most Common Anemometer Problems
“The anemometer head is tilted when I mount the anemometer.”
With the Allen wrench provided in the supplied hardware, loosen the screws holding the anemometer
head on the arm. (The screws are on the bottom of the anemometer head, by the wind cups.) Turn the
anemometer head so it is straight and then tighten the screws.
“The wind cups are spinning but my console displays 0 mph.”
The signal from the wind cups may not be making it back to the display.
Remove the cups from the anemometer (loosen the set screw). Put the cups back onto the shaft and
make sure to slide them up the shaft as far as possible. Check your cables for visible nicks and cuts. Look
for corrosion in the WIND connector on the SIM and on splices in the cable. If using an extension cable,
5
This picture is courtesy of Davis Instruments; www.davisnet.com
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remove it and test using only the anemometer cable. Contact Technical Support and ask for a wind test
cable if the problem has not been resolved.
Note: If the anemometer is sending no data, the wind display indicates 0 speed and a north direction.
“The wind direction is stuck on north, or displays dashes.”
It is likely that there is a short somewhere between the wind vane and the display. Check the cables for
visible nicks and cuts. Look for corrosion in the “WIND” jack on the SIM and on splices in the cable (if
any). If possible, remove any extensions and try it with the anemometer cable only. If none of these
steps get the wind direction working, contact Technical Support and ask for a wind test cable.
“The wind cups don’t spin or don’t spin as fast as they should.”
The anemometer may be located where wind is blocked by something, or there may be friction
interfering with the cups’ rotation. Remove the wind cups (loosen the set screw) and clear out any bugs
or debris. Turn the shaft the cups rotate on. If it feels gritty or stiff, contact Davis Technical Support.
Note: Do not lubricate the shaft or bearings in any way. When replacing the cups, make sure they are
not rubbing against any part of the anemometer head.
“Readings aren’t what I expected them to be.”
Comparing data from your ISS to measurements from TV, radio, newspapers, or a neighbor is NOT a
valid method of verifying your readings. Readings can vary considerably over short distances. How you
cite the ISS and anemometer can also make a big difference. If you have questions, contact Technical
Support.
Troubleshooting Wireless ISS Reception
If the console isn’t displaying data from the ISS, perform the following steps:
1. Verify that the console is powered and is not in Setup Mode.
2. Make sure that all ISS sensor cables are firmly connected to the SIM and the ISS battery is properly
installed.
3. Walk around the room with the console, standing for a few moments in various locations, to see if
you are picking up signals from the ISS. Look on the screen’s lower right corner. An “X” toggles on and
off when the console receives a transmission.
4. If you do not see the “X” slowly blinking, no matter where you stand with the console, put your ISS in
Test Mode.
• The DIP switch #4 on the SIM is the Test Mode switch. Switch it to the ON position, using a ballpoint
pen or paper clip.
• An LED indicator light on the SIM flashes each time the ISS transmits, which is about once every
2.5 seconds.
Note: If the LED is flashing rapidly, call technical support at Davis Instruments.
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5. If the LED remains dark, there is a problem with the ISS transmitter, call technical support at Davis
Instruments.
6. If the LED flashes repeatedly but your console isn’t picking up a signal anywhere in the room, it could
be related to one of the following causes:
• You changed the ISS Transmitter ID at the ISS or console, but not at both.
• Reception is being disrupted by frequency interference from outside sources.
Interference has to be strong to prevent the console from receiving a signal while in the same room as
the ISS. In high-interference environments, it may be preferable to install the Cabled Vantage Pro2.
• There is a problem with the console.
7. If a problem with receiving the wireless transmission still exists, call technical support at Davis
Instruments.
8. When you are finished testing wireless transmission, set DIP switch # 4 to OFF to take the SIM out of
Test Mode.
Campbell data logger:
If the data logger appears to be having problems, check the power source, the connections to the logger
and the cable that runs from the logger to the laptop.
Futek load sensors:
If the load sensors appear to be having problems, check the connections to the data logger and the load
platform.
Huskeflux heat flux sensor:
If the heat flux sensor appears to be having problems, check the connections to the data logger.
Decagon moisture sensor:
If the moisture sensor appears to be having problems, check the connections to the data logger.
Type-T Thermocouples:
If the thermocouples appear to be having problems, check the connections to the data logger.
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Appendix A – Model Specifications
Davis weather station:
Wireless Vantage Pro2™ (Model 6152)
Integrated Sensor Suite (ISS)
Operating Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . -40° to +150°F (-40° to +65°C)
Non-operating Temperature . . . . . . . . . . . . . . . . . . . . . . . -40° to +158°F (-40° to +70°C)
Current Draw (ISS SIM only) . . . . . . . . . . . . . . . . . . . . . . 0.14 mA (average), 30 mA (peak) at 4 to 6 VDC
Solar Power Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 Watts (ISS SIM), plus 0.75 Watts (Fan-Aspirated)
Battery (ISS SIM /Fan-Aspirated) . . . . . . . . . . . . . . . . . . . CR-123 3-Volt Lithium cell / 2 - 1.2 Volt NiCad C-cells
Battery Life (3-Volt Lithium cell) . . . . . . . . . . . . . . . . . . . . 8 months without sunlight - greater than 2 years depending on solar charging
Battery Life (NiCad C-cells) . . . . . . . . . . . . . . . . . . . . . . . 1 year
Fan Aspiration Rate (Fan-Aspirated Only) . . . . . . . . . . . . 190 feet/min. (0.9 m/s) (full sun), 80 feet/min. (0.4 m/s) (battery only) (intake flow rate)
500 feet/min. (2.5 m/s) (full sun), 280 feet/min. (1.4 m/s) (battery only) (sensor chamber flow rate)
Connectors, Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modular RJ-11
Cable Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-conductor, 26 AWG
Cable Length, Anemometer . . . . . . . . . . . . . . . . . . . . . . . 40’ (12 m) (included) 540’ (165 m) (maximum recommended)
Wind Speed Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . .Wind cups with magnetic switch
Wind Direction Sensor . . . . . . . . . . . . . . . . . . . . . . . . . .Wind vane with potentiometer
Rain Collector Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tipping bucket, 0.01" per tip (0.2 mm with metric rain adapter), 33.2 in2 (214 cm2)
collection area
Temperature Sensor Type . . . . . . . . . . . . . . . . . . . . . . . . PN Junction Silicon Diode
Relative Humidity Sensor Type . . . . . . . . . . . . . . . . . . . . Film capacitor element
Housing Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . UV-resistant ABS, ASA plastic
ISS Dimensions:
Product # (Length x Width x Height) Package Weight
6152 11.00" x 9.38" x 14.00"
(279 mm x 238 mm x 355 mm)
5.7 lbs. (2.6 kg)
6162 6.1 lbs. (2.6 kg)
6153 11.00" x 9.38" x 21.00"
(279 mm x 238 mm x 533 mm)
8.6 lbs. (3.9 kg)
6163 9 lbs. (4.1 kg)
Vantage Pro2™
Console
Console Operating Temperature . . . . . . . . . . . . . . . . . . . +32° to +140°F (0° to +60°C)
Non-Operating (Storage) Temperature . . . . . . . . . . . . . . . +14° to +158°F (-10° to +70°C)
Current Draw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 mA average, 30 mA peak, (add 120 mA for display lamps, add 0.125 mA for each
optional wireless transmitter received by the console) at 4 - 6 VDC
AC Power Adapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 VDC, 300 mA, regulated
Batteries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 C-cells
Battery Life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . up to 9 months
Connectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Modular RJ-11
Housing Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .UV-resistant ABS plastic
Console Display Type . . . . . . . . . . . . . . . . . . . . . . . . . . . LCD Transflective
Display Backlight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LEDs
Dimensions (console: length x width x height, display length x height)
Console with antenna down . . . . . . . . . . . . . . . . . . . 10.625" x 6.125" x 1.625" (270 mm x 156 mm x 41 mm)
Console with antenna extended up . . . . . . . . . . . . . . 10.625" x 9.625" x 1.625" (270 mm x 245 mm x 41 mm)
Display . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.94" x 3.375" (151 mm x 86 mm)
Weight (with batteries) . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.88 lbs. (.85 kg)
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Campbell data logger:
Model CR 1000
PROGRAM EXECUTION RATE
10 ms to 30 min. @ 10 ms increments
ANALOG INPUTS
8 differential (DF) or 16 single-ended (SE) individually configured. Channel expansion provided by AM16/32B and AM25T multiplexers.
RANGES and RESOLUTION: Basic resolution (Basic Res) is the A/D resolution of a single conversion. Resolution of DF measurements with input
reversal is half the Basic Res.
Input Referred Noise Voltage
Input DF Basic
Range (mV)1 Res (μV)2 Res (μV)
±5000 667 1333
±2500 333 667
±250 33.3 66.7
±25 3.33 6.7
±7.5 1.0 2.0
±2.5 0.33 0.67
1Range overhead of ~9% exists on all ranges to guarantee that full-scale values will not cause over-range. 2Resolution of DF measurements
with input reversal.
ACCURACY3:
±(0.06% of reading + offset), 0° to 40°C
±(0.12% of reading + offset), -25° to 50°C
±(0.18% of reading + offset), -55° to 85°C (-XT only)
3The sensor and measurement noise are not included and the offsets are the following:
Offset for DF w/input reversal = 1.5·Basic Res + 1.0 μV
Offset for DF w/o input reversal = 3·Basic Res + 2.0 μV
Offset for SE = 3·Basic Res + 3.0 μV
INPUT NOISE VOLTAGE: For DF measurements with input reversal on ±2.5 mV input range; digital resolution dominates for higher ranges.
250 μs Integration: 0.34 μV RMS
50/60 Hz Integration: 0.19 μV RMS
MINIMUM TIME BETWEEN VOLTAGE
MEASUREMENTS: Includes the measurement time and conversion to engineering units. For voltage measurements, the CR1000 integrates the
input signal for 0.25 ms or a full 16.66 ms or 20 ms line cycle for 50/60 Hz noise rejection. DF measurements with input reversal incorporate
two integrations with reversed input polarities to reduce thermal offset and common mode errors and therefore take twice as long.
250 μs Analog Integration: ~1 ms SE
1/60 Hz Analog Integration: ~20 ms SE
1/50 Hz Analog Integration: ~25 ms SE
INPUT LIMITS: ±5 V
DC COMMON MODE REJECTION: >100 dB
NORMAL MODE REJECTION: 70 dB @ 60 Hz when using 60 Hz rejection
SUSTAINED INPUT VOLTAGE W/O DAMAGE: ±16 Vdc max.
INPUT CURRENT: ±1 nA typical, ±6 nA max. @ 50°C; ±90 nA @ 85°C
INPUT RESISTANCE: 20 G ohms typical
ACCURACY OF BUILT-IN REFERENCE JUNCTION
THERMISTOR (for thermocouple measurements):
±0.3°C, -25° to 50°C
±0.8°C, -55° to 85°C (-XT only)
ANALOG OUTPUTS
3 switched voltage, active only during measurement, one at a time.
RANGE AND RESOLUTION: Voltage outputs programmable between ±2.5 V with 0.67 mV resolution.
ACCURACY: ±(0.06% of setting + 0.8 mV), 0° to 40°C
±(0.12% of setting + 0.8 mV), -25° to 50°C
±(0.18% of setting + 0.8 mV), -55° to 85°C (-XT only)
CURRENT SOURCING/SINKING: ±25 mA
RESISTANCE MEASUREMENTS
MEASUREMENT TYPES: The CR1000 provides radiometric measurements of 4- and 6-wire full bridges, and 2-, 3-, and 4-wire half bridges.
Precise, dual polarity excitation using any of the 3 switched voltage excitations eliminates dc errors.
RATIO ACCURACY4: Assuming excitation voltage of at least 1000 mV, not including bridge resistor error. ±(0.04% of voltage reading + offset)/Vx
4The sensor and measurement noise are not included and the offsets are the following:
Offset for DF w/input reversal = 1.5·Basic Res + 1.0 μV
Offset for DF w/o input reversal = 3·Basic Res + 2.0 μV
Offset for SE = 3·Basic Res + 3.0 μV
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Offset values are reduced by a factor of 2 when excitation reversal is used.
PERIOD AVERAGING MEASUREMENTS
The average period for a single cycle is determined by measuring the average duration of a specified number of cycles. The period resolution is
192 ns divided by the specified number of cycles to be measured; the period accuracy is ±(0.01% of reading + resolution). Any of the 16 SE
analog inputs can be used for period averaging. Signal limiting is typically required for the SE analog channel.
INPUT FREQUENCY RANGE:
Input Signal (peak to peak)5 Min. Max6
Range Min Max Pulse W. Freq.
±2500 mV 500 mV 10 V 2.5 μs 200 kHz
±250 mV 10 mV 2 V 10 μs 50 kHz
±25 mV 5 mV 2 V 62 μs 8 kHz
±2.5 mV 2 mV 2 V 100 μs 5 kHz
5The signal is centered at the data logger ground.
6The maximum frequency = 1/(Twice Minimum Pulse Width) for 50% of duty cycle signals.
PULSE COUNTERS
Two 24-bit inputs selectable for switch closure, high frequency pulse, or low-level AC.
MAXIMUM COUNTS PER SCAN: 16.7x106
SWITCH CLOSURE MODE:
Minimum Switch Closed Time: 5 ms
Minimum Switch Open Time: 6 ms
Max. Bounce Time: 1 ms open w/o being counted
HIGH-FREQUENCY PULSE MODE:
Maximum Input Frequency: 250 kHz
Maximum Input Voltage: ±20 V
Voltage Thresholds: Count upon transition from below 0.9 V to above 2.2 V after input filter with 1.2 μs time constant.
LOW-LEVEL AC MODE: Internal AC coupling removes
AC offsets up to ±0.5 V.
Input Hysteresis: 12 mV @ 1 Hz
Maximum ac Input Voltage: ±20 V
Minimum ac Input Voltage:
Sine wave (mV RMS) Range (Hz)
20 1.0 to 20
200 0.5 to 200
2000 0.3 to 10,000
5000 0.3 to 20,000
DIGITAL I/O PORTS
8 ports software selectable, as binary inputs or control outputs. C1-C8 also provide edge timing, subroutine interrupts/wake up, switch closure
pulse counting, high frequency pulse counting, asynchronous communications (UART), SDI-12 communications, and SDM communications.
HIGH-FREQUENCY PULSE MAX: 400 kHz
SWITCH CLOSURE FREQUENCY MAX: 150 Hz
OUTPUT VOLTAGES (no load): high 5.0 V ±0.1 V; low <0.1
OUTPUT RESISTANCE: 330 ohms
INPUT STATE: high 3.8 to 16 V; low -8.0 to 1.2 V
INPUT HYSTERESIS: 1.4 V
INPUT RESISTANCE: 100 k ohms
SERIAL DEVICE/RS-232 SUPPORT: 0 to 5 V UART
SWITCHED 12 V
One independent 12 V unregulated sources switched on and off under program control. Thermal fuse hold current = 900 mA @ 20°C, 650 mA
@ 50°C, 360 mA @ 85°C.
SDI-12 INTERFACE SUPPORT
Control ports 1, 3, 5, and 7 may be configured for SDI-12 asynchronous communications. Up to ten SDI-12 sensors are supported per port. It
meets SDI-12 Standard version 1.3 for data logger mode.
CE COMPLIANCE
STANDARD(S) TO WHICH CONFORMITY IS
DECLARED: IEC61326:2002
CPU AND INTERFACE
PROCESSOR: Renesas H8S 2322 (16-bit CPU with 32-bit internal core)
PROTOCOLS SUPPORTED: PakBus, Modbus, DNP3, FTP, HTTP, XML, POP3, SMTP, Telnet, NTCIP, NTP, SDI-12, SDM
MEMORY: 2 MB of Flash for operating system; 4 MB of battery-backed SRAM for CPU usage, program storage and data storage.
CLOCK ACCURACY: ±3 min. per year
PARALLEL INTERFACE: 40-pin interface for attaching
CompactFlash or Ethernet peripherals
SERIAL INTERFACES: CS I/O port is used to interface with Campbell Scientific peripherals; RS-232
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DCE port is for battery-powered computer or nonCSI modem connection. Baud rates are selectable from 300 bps to 115.2 kbps. ASCII protocol is one start bit, one stop bit, eight data bits, and
no parity.
SYSTEM POWER REQUIREMENTS
VOLTAGE: 9.6 to 16 Vdc (reverse polarity protected)
TYPICAL CURRENT DRAIN:
Sleep Mode: ~0.6 mA
1 Hz Scan (8 diff. meas., 60 Hz rej., 2 pulse meas.) w/RS-232 communication: 19 mA w/o RS-232 communication: 4.2 mA
1 Hz Scan (8 diff. meas., 250 μs integ., 2 pulse meas.) w/RS-232 communication: 16.7 mA w/o RS-232 communication: 1 mA
100 Hz Scan (4 diff. meas., 250 μs integ.) w/RS-232 communication: 27.6 mA w/o RS-232 communication: 16.2 mA
CR1000KD CURRENT DRAIN:
Inactive: negligible
Active w/o backlight: 7 mA
Active w/backlight: 100 mA
EXTERNAL BATTERIES: 12 Vdc nominal
PHYSICAL
MEASUREMENT & CONTROL MODULE SIZE:
8.5" x 3.9" x 0.85" (21.6 x 9.9 x 2.2 cm)
CR1000WP WIRING PANEL SIZE: 9.4" x 4" x 2.4"
(23.9 x 10.2 x 6.1 cm); additional clearance required for serial cable and sensor leads.
WEIGHT: 2.1 lbs (1 kg)
Decagon moisture sensor:
Accuracy:
Mineral Soil:
±3% VWC, All mineral soils
±1-2% VWC soil specific calibration, up to 8
dS/m
Rockwool: ±3% VWC, 0.5 to 8 dS/m
Potting Soil: ±3% VWC, 3 to 14 dS/m
Resolution:
0.1% VWC (mineral soil)
0.25% VWC (rockwool)
Range:
0-100% VWC
Dimensions:
8.9 x 1.8 x 0.7 cm
Cable Length:
Measurement Time:
5 m, custom cable lengths available upon
request
10 ms
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Power:
2.5 - 3.6 V @ 10 mA. Output proportional to
input voltage. 2.5 V and 3 V excitations
supported with calibration equations
Output:
Voltage, correlated linearly (soil) or polynomially
(growing media) with VWC
Temperature:
-40°C to +50°C
Connector Types:
3.5 mm "stereo" plug or stripped and tinned
lead wires (3)
Data logger Compatibility
Decagon: Em50, EM50R, ProCheck, ECH2O
(not exclusive):
Check, Em5b
Campbell Scientific: CR10X, 21X, 23X, CR1000,
CR3000, etc.
Other: Any data acquisition system capable of
switched 2 to 3.6 V excitation and single ended
voltage measurement at 12 bit or better
resolution.
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Futek load sensors:
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Huskeflux heat flux sensor:
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Appendix B– Additional Information
Davis weather station: Calibrating, Setting, and Clearing Variables
To fine-tune your station, you can calibrate most of the weather variables. For example, if your outside
temperature seems consistently too high or too low, you can enter an offset to correct the deviation.
Calibrating Temperature and Humidity
You can calibrate inside & outside temperature, inside & outside humidity, as well as any extra
temperature/humidity sensor readings you have transmitting to your Vantage Pro2.
1. Select a variable to be calibrated. See “Selecting Weather Variables” on page XXX.
2. Press and release 2ND, then press and hold SET. After a moment, the variable you’ve selected begins
to blink. Keep holding SET until the Calibration Offset message displays in the ticker. The ticker displays
the current calibration offset.
3. Press the + and - keys to add or subtract from the temperature offset value. Inside and outside
temperature are calibrated in 0.1° F or 0.1° C increments, up to a maximum offset of +12.7 (°F or °C) and
a minimum offset of -12.8 (°F or °C). The variable will change value and the ticker will show the offset
you’ve entered.
4. Press DONE to exit calibration.
Calibrate Wind Direction Reading
If the anemometer arm cannot be mounted pointing to true north, use this procedure to correct the
wind direction console reading.
1. Check the current direction of the wind vane on the anemometer. Compare it to the wind direction
reading on the console.
2. Press WIND as necessary to display the wind direction in degrees.
3. Press and release 2ND, then press and hold SET.
4. The wind direction variable will begin to blink.
5. Continue holding the key until the CAL message appears in the ticker. The ticker displays the current
wind direction calibration value.
6. Press the < and > keys to select digits in the anemometer’s current reading.
7. Press the + and - keys to add/subtract from the anemometer reading.
8. Repeat steps 6 and 7 until you have entered the offset value from Step 1.
9. Press DONE to exit calibration.
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Calibrating Barometric Pressure
Before calibrating the barometric pressure, be sure the station is set to the correct elevation. See
“Screen 10: Elevation” on page XXX for more information.
1. Press BAR to select barometric pressure.
2. Press and release 2ND, then press and hold SET.
The pressure variable blinks.
3. Continue holding the key until the ticker reads “set barometer . . . ”.
4. Press the < and > keys to select digits in the variable.
5. Press + and - keys to add to or subtract from the digit’s value.
6. Press DONE to exit calibration.
Setting Weather Variables
You can set values for the following weather variables:
• Daily Rain—Sets the daily rain total. Monthly and yearly rain totals are updated.
• Monthly Rain—Sets the current month’s total rain. Does not affect yearly rain total.
• Yearly Rain—Sets the current year’s rain total.
• Daily ET (Evapotranspiration)—Sets the daily ET total. Monthly and yearly
ET totals are updated.
• Monthly ET—Sets the current month’s ET. Does not affect yearly total.
• Yearly ET—Sets the current year’s total ET.
To set a weather variable’s value:
1. Select the variable you wish to change.
2. Press and release 2ND, then press and hold SET. The variable blinks.
3. Keep holding SET until all digits are lit and only one digit is blinking.
4. Press the < or > keys to select digits in the value.
5. Press the + and - keys to add to or subtract from the selected digit.
6. When you are finished, press DONE to exit.
Clearing Weather Variables
The following weather variables can be cleared:
• Barometer—Clears any pressure offset used to calibrate the station, and the elevation entry.
• Wind—Clears the wind direction calibration.
• Daily rain—Clearing the daily rain value is reflected in the daily rain total, the last 15 minutes of rain,
the last three hours of rain sent to the forecast algorithm, the umbrella icon, and the monthly and yearly
rain totals. Clear the daily rain total if the station accidentally recorded rain when the ISS was installed.
• Monthly rain—Clears the monthly rain total. Does not affect the yearly rain total.
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• Yearly rain—Clears the yearly rain total.
• Daily ET—Clears daily ET and subtracts the old daily ET total from the monthly and yearly ET totals.
• Monthly ET—Clears the current monthly ET total. Does not affect the yearly ET total.
• Yearly ET—Clears the current yearly ET total.
To clear a single weather variable:
1. Select the weather variable. See “Selecting Weather Variables” on page XXX.
2. Press and release 2ND, then press and hold CLEAR.
The variable you’ve chosen blinks. Keep holding the key until the value changes to zero or, in the case of
the barometer, the raw barometer value. Clearing the barometer value also clears the elevation setting.
Clear All Command
This command clears all stored high and low weather data including monthly and yearly highs and lows
and clears alarm settings all at once.
1. Press WIND on the console.
2. Press 2ND then press and hold CLEAR for at least six seconds.
3. Release CLEAR when “CLEARING NOW” displays at the bottom of the console’s screen.
Appendix C– Sample data
Sample of data collected from the Davis weather station.
Date
Time
Te
mp
Out
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
12:01
AM
12:02
AM
12:03
AM
12:04
AM
12:05
AM
12:06
AM
12:07
AM
12:08
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
Hi
Te
mp
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
Low Ou
t
Te
Hu
mp m
10. 77
2
10. 77
2
10. 78
2
10. 77
2
10. 77
3
10. 78
3
10. 77
3
10. 77
De
w
Pt.
Wi
nd
Dir
6.4
Win
d
Spe
ed
0.9
Hi
Hi
Spe
ed
1.3
Dir
0.9
E
0.9
E
E
Wi
nd
Ru
n
0.0
5
0.0
3
0.0
3
0
6.4
0.4
E
6.6
0.4
E
6.4
0
0.4
E
6.4
0
---
0
0
---
6.6
0
---
0
0
---
6.4
0
---
0
0
---
6.4
0.4
EN
0.0
1.3
EN
ESE
E
Wi
nd
Chil
l
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
Hea
t
Ind
ex
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
TH
W
Ind
ex
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
Bar
760
.7
760
.7
760
.7
760
.7
760
.7
760
.7
760
.7
760
58 | P a g e
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
5/11/2
010
AM
12:09
AM
12:10
AM
12:11
AM
12:12
AM
12:13
AM
12:14
AM
12:15
AM
12:16
AM
12:17
AM
12:18
AM
12:19
AM
12:20
AM
12:21
AM
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
E
EN
E
EN
E
EN
E
E
3
0
0.0
3
0.0
3
0
0.9
0.4
E
EN
E
EN
E
EN
E
E
0.9
E
1.3
77
6.4
0
0.9
77
6.4
0.4
76
6.2
0.4
77
6.4
0
77
6.4
0.4
76
6.2
0.4
EN
E
ESE
76
6.2
0
ESE
0.0
3
0.0
3
0
76
6.2
0
---
0
0
ES
E
ES
E
---
77
6.4
0
---
0
0
---
77
6.4
0
---
0
0
---
77
6.4
0
---
0
0
---
77
6.4
0
---
0
0
---
77
6.4
0
---
0
0
---
0.9
0.4
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
10.
3
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
10.
2
.7
760
.8
760
.8
760
.8
760
.8
760
.8
760
.8
760
.8
760
.7
760
.8
760
.8
760
.8
760
.8
760
.8
Figure 5: Sample data set from the Davis weather station logger.
Sample of data collected from the CR1000.
TIMEST
AMP
TS
5/10/20
10 0:00
5/10/20
10 0:00
5/10/20
10 0:00
REC
ORD
RN
203
43
203
44
203
45
Bat
V
Vol
ts
Sm
p
12.
07
12.
07
12.
07
MoistureAvg
Flux
mV
Load
Cell 1
mV
Load
Cell 2
mV
Load
Cell 3
mV
Load
Cell 4
mV
Temp
_C(1)
Deg C
Temp
_C(2)
Deg C
Temp
_C(3)
Deg C
Volumetric
Water
content
Avg
Smp
Smp
Smp
Smp
Smp
Smp
Smp
Smp
0.288
0
7.832
10.38
11.57
9.63
12.17
15.49
16.49
0.288
0
7.832
10.38
11.57
9.63
12.17
15.49
16.48
0.288
0
7.832
10.38
11.57
9.63
12.17
15.49
16.5
59 | P a g e
5/10/20
10 0:00
5/10/20
10 0:00
5/10/20
10 0:00
5/10/20
10 0:01
5/10/20
10 0:01
5/10/20
10 0:01
5/10/20
10 0:01
5/10/20
10 0:01
5/10/20
10 0:01
5/10/20
10 0:02
5/10/20
10 0:02
5/10/20
10 0:02
5/10/20
10 0:02
5/10/20
10 0:02
203
46
203
47
203
48
203
49
203
50
203
51
203
52
203
53
203
54
203
55
203
56
203
57
203
58
203
59
12.
07
12.
07
12.
07
12.
07
12.
06
12.
07
12.
07
12.
07
12.
07
12.
07
12.
07
12.
07
12.
07
12.
06
0.288
0
7.832
10.38
11.57
9.63
12.17
15.5
16.5
0.288
0
7.832
10.38
11.58
9.63
12.18
15.5
16.5
0.288
0
7.832
10.38
11.57
9.63
12.18
15.5
16.51
0.288
0
7.832
10.38
11.57
9.63
12.19
15.51
16.51
0.288
0
7.832
10.38
11.57
9.63
12.17
15.48
16.48
0.288
0
7.832
10.38
11.57
9.63
12.17
15.48
16.49
0.288
0
7.832
10.38
11.57
9.63
12.17
15.49
16.5
0.288
0
7.832
10.38
11.57
9.63
12.18
15.49
16.5
0.288
0
7.832
10.38
11.57
9.63
12.19
15.49
16.5
0.288
0
7.832
10.38
11.57
9.63
12.19
15.49
16.5
0.288
0
7.832
10.38
11.57
9.63
12.2
15.49
16.51
0.288
0
7.832
10.38
11.57
9.63
12.2
15.5
16.51
0.288
0
7.832
10.38
11.57
9.63
12.18
15.48
16.48
0.288
0
7.832
10.38
11.57
9.63
12.19
15.48
16.49
Figure 6: Sample data set from the CR1000 logger.
60 | P a g e
Appendix D– Additional code
Davis weather station Matlab code:
function showWeathertest(fname)
% showWeather Plot weather data from CSV file
if nargin<1, fname='WS0516-0522.csv'; end
[dstr,tstr,t,wind_dir,hi_dir,D,colheads] = readWeatherCSV(fname);
% Open the Campbell logger file
g = fopen('CL0516-0522.csv','rt');
% Open surface temperature file
h = fopen('ST0516-0522.csv','rt');
% Open 2 cm depth temperature file
k = fopen('d2T0516-0522.csv','rt');
% -- Build format string for scanning columns of strings and numbers
frmt_strng = ['%s%s',repmat('%f',1,10)];
% -- Read entire file into a cell array
A = textscan(g,frmt_strng,'delimiter',',');
fclose(g);
% -- Initialize output arrays
dst = A{1,1};
% date string in column 1
tst = A{1,2};
% time string in column 2
q = size(dst,1);
% number of rows of data
% --- Convert date and time to datenum for plotting
tvl = zeros(q,1); % column of times in datenum format
dC = regexp( dst, '/', 'split'); % split into three cell arrays for month/day/year
tC = regexp( tst, ':', 'split'); % split into two cell arrays for hh:mm
% -- The only klutzy part is the scalar loop. I don't (yet) know how to
% vectorize the time conversion. This is the slowest part of the entire function
for i=1:q
tvl(i) = datenum( str2double(dC{i}{3}), str2double(dC{i}{1}), str2double(dC{i}{2}), ...
str2double(tC{i}{1}), str2double(tC{i}{2}), 0 );
end
% -- Build format string for scanning columns of strings and numbers
formt_strng = ['%f%s%s%f'];
% -- Read entire file into a cell array
B = textscan(h,formt_strng,'delimiter',',');
fclose(h);
% -- Initialize output arrays
61 | P a g e
dstrin = B{1,2};
tstrin = B{1,3};
r = size(dstrin,1);
% date string in column 1
% time string in column 2
% number of rows of data
% --- Convert date and time to datenum for plotting
tevl = zeros(r,1); % column of times in datenum format
dS = regexp( dstrin, '/', 'split'); % split into three cell arrays for month/day/year
tS = regexp( tstrin, ':', 'split'); % split into two cell arrays for hh:mm
% -- The only klutzy part is the scalar loop. I don't (yet) know how to
% vectorize the time conversion. This is the slowest part of the entire function
for i=1:r
tevl(i) = datenum( str2double(dS{i}{3}), str2double(dS{i}{2}), str2double(dS{i}{1}), ...
str2double(tS{i}{1}), str2double(tS{i}{2}), 0 );
end
% -- Read entire file into a cell array
Q = textscan(k,formt_strng,'delimiter',',');
fclose(k);
% -- Initialize output arrays
dstring = Q{1,2};
% date string in column 1
tstring = Q{1,3};
% time string in column 2
u = size(dstring,1);
% number of rows of data
% --- Convert date and time to datenum for plotting
teval = zeros(u,1); % column of times in datenum format
dd2 = regexp( dstring, '/', 'split'); % split into three cell arrays for month/day/year
td2 = regexp( tstring, ':', 'split'); % split into two cell arrays for hh:mm
% -- The only klutzy part is the scalar loop. I don't (yet) know how to
% vectorize the time conversion. This is the slowest part of the entire function
for i=1:u
teval(i) = datenum( str2double(dd2{i}{3}), str2double(dd2{i}{2}), str2double(dd2{i}{1}), ...
str2double(td2{i}{1}), str2double(td2{i}{2}), 0 );
end
% Convert remaining data from the Campbell cell array to the P matrix one column at a time.
P = zeros(q,8);
P(:,1) = A{:,5};
P(:,2) = A{:,6};
P(:,3) = A{:,7};
P(:,4) = A{:,8};
P(:,5) = A{:,9};
P(:,6) = A{:,10};
P(:,7) = A{:,11};
P(:,8) = A{:,12};
% Convert remaining data from the Lascar cell arrays to the T and V matrices one column at a time.
T = zeros(r,1);
V = zeros(u,1);
T(:,1) = B{:,4};
62 | P a g e
V(:,1) = Q{:,4};
% Plot Surface temperature and Ambient air temperature
figure
plot(tevl,T(:,1),'.',t,D(:,1),'.')
datetick('x');
xlabel('Date');
ylabel('Temperature (deg C)')
legend('Surface Temperature','Ambient Air Temperature')
ST = T(:,1);
AT = D(:,1);
while length(AT) > length(ST)
AT(length(AT)) = [];
end
diff = ST-AT;
% Plot temperature difference
figure
plot(tevl,diff,'.')
datetick('x');
xlabel('Date');
ylabel('Temperature Difference (deg C)')
% Plot the temperatures of the tray
figure
plot(tvl,P(:,8),'.',tvl,P(:,7),'.',teval,V(:,1),'.',tevl,T(:,1),'.')
datetick('x');
xlabel('Date');
ylabel('Temperature (deg C)')
legend('Bottom Tray Temperature','Middle Tray Temperature','2 cm Depth Temperature','Surface
Temperature')
% For R-value enter scalar vlaues
rhow = 1000;
rhob = 400;
Cw = 4.1855;
d = 0.0508;
% Calculate the soil water content on a mass basis using soil moisture
thetam = (rhow/rhob)*P(:,1);
% Create a matrix for the constant specific heat of dry soil
b = length(P(:,1));
Csubd = ones(b,1);
Cd = 1.53*Csubd;
% Calculate the heat capacity of the moist soil
Cs = rhob*(Cd + Cw*thetam);
Cs(1) = [];
% Calculate the average temperature from the heat flux sensor to the bottom
63 | P a g e
% of the tray. To find the temporal temperature difference create two
% matrices. The "i+1" matrix is the avg. temp. matrix with the first value
% removed. The "i" matrix is the avg. temp. matrix with the last value
% removed.
Tavg = (P(:,8) + P(:,7))/2;
T2 = Tavg;
T2(1) = [];
T1 = Tavg;
a = length(T1);
T1(a) = [];
% Calculate the stored flux in the soil
S = ((T2 - T1).*Cs*d)/60;
soilflux = P(:,2);
soilflux(1) = [];
% Calculate the effective heat flux
G = length(soilflux);
flux = zeros(G,1);
for i = 1:length(soilflux)
if soilflux(i) < 2 && soilflux(i) > -2
flux(i) = 1000;
else
flux(i) = soilflux(i)+S(i);
end
end
% Assign variables to the bottom temperature and 2 cm depth temperature
Tbot = P(:,8);
Tbot(1) = [];
Td2 = V(:,1);
% Ensure that the size of the matrices are equal
while length(Td2) > length(Tbot)
Td2(1) = [];
end
while length(Td2) < length(Tbot)
Tbot(1) = [];
end
while length(Td2) < length(flux)
flux(1) = [];
end
% Calculate R-value
R = (Td2-Tbot)./flux;
tR = tvl;
while length(tR) > length(Td2)
tR(1) = [];
end
Rv = 5.678263*R;
STemp = (9/5)*T(:,1)+32;
Rval = 0;
for i = 1:length(Rv)
Rval = Rv(i)+Rval;
64 | P a g e
end
AverageRvalue = Rval/length(Rv)
Surftemp = 0;
for i = 1:length(STemp)
Surftemp = STemp(i)+Surftemp;
end
AverageSurfacetemp = Surftemp/length(STemp)
% Plot the R-value with soil water content on a volume basis
figure
plot(tR,Rv,'.')
datetick('x');
xlabel('Date')
ylabel('R-value (h*ft^2*deg F/Btu) vs. Surface Temperature (deg F)')
legend('R-value')
% For water run-off identify the dimensions of the tray
sidelength = 0.6096;
depth = .1016;
% Calculate the voume of the tray
Vtray = depth*sidelength^2;
% Calculate the mass of water entering the system
min = (D(:,13)/1000)*sidelength^2*rhow;
% Find the total mass of the system
Load = P(:,3) + P(:,4) + P(:,5) + P(:,6);
% Find the mass of the soil in the test tray
dens = length(Load);
densit = ones(dens,1);
msoil = densit*rhob*Vtray;
% Create a matrix for moisture values
mstoremoist = P(:,1);
moist = 0;
for i = 1:length(mstoremoist)
moist = mstoremoist(i)+moist;
end
AverageMoisture = moist/length(mstoremoist)
% Create a matrix for water run-off based on whether the tray system is
% fully saturated or not
moutmoist = zeros(b,1);
for i = 1:length(min)
if mstoremoist(i) >= 0.3
moutmoist(i) = min(i);
else
moutmoist(i) = 0;
end
end
65 | P a g e
% Plot the rainfall and water run-off
figure
plot(t,min,'.',tvl,moutmoist,'.')
datetick('x');
xlabel('Date');
ylabel('Water Volume (m^3/m^3)')
legend('Rainfall','Water Run-off by Soil Moisture')
% For evapotranspiration find the mass of water in the system. To find the
% temporal mass difference create two matrices. The "i+1" matrix is the
% water mass matrix with the first value removed. The "i" matrix is the
% water mass matrix with the last value removed.
mstrld = Load-msoil;
msl2 = mstrld;
msl2(1) = [];
msl1 = mstrld;
msl1(dens) = [];
% Ensure that the difference is only being caculated when the tray is below
% the maximum saturation level. Negative values will also be removed as
% well as unreasonable values (caused by chickens).
for i = 1:length(msl1)
if mstoremoist(i) <= 0.29
EvapT(i) = msl1(i) - msl2(i);
else
EvapT(i) = 0;
end
end
for i = 1:length(EvapT)
if EvapT(i) < 0
EvapT(i) = 0;
end
end
for i = 1:length(EvapT)
if EvapT(i) >= 0.25
EvapT(i) = 0;
end
end
for i = 1:length(EvapT)
if min(i) > 0
EvapT(i) = 0;
end
end
% Because of the matrix size change for the difference calculation, the
% time matrix is modified
tevap = tvl;
tevap(1) = [];
% In order for the temperature data to be meaningful in this graph it must
% be changed to a different scale
scltemp = D(:,1)/20;
% Plot evapotranspiration with it scontributing factors
figure
66 | P a g e
plot(tevap,EvapT,'.',t,min,'.',tvl,P(:,1),'.',t,scltemp,'.')
datetick('x');
xlabel('Date');
ylabel('Evapotranspiration vs. Contributing Factors')
legend('Evapotranspiration','Rainfall','Soil Moisture','Ambient Air Temperature')
kgin = (D(:,13)/1000)*39.37;
kgout = (moutmoist/(sidelength^2*rhow))*39.37;
% Find the total rainfall
Rf = 0;
for i = 1:length(min)
Rf = kgin(i)+Rf;
end
TotalRainfall = Rf
% Find total drainage
Drain = 0;
for i = 1:length(moutmoist)
Drain = kgout(i)+Drain;
end
TotalDrainage = Drain
% Find total Evapotranspiration
Evap = 0;
for i = 1:length(EvapT)
Evap = EvapT(i)+Evap;
end
TotalEvapotranspiration = Evap/1000
CR1000 data logger code:
'Declare Variables and Units
Public BattV
'Decagon ECHCO EC-5 Moisture sensor
Public Moisture
'Hukseflux Flux sensor
Public Flux
'Mass balance load cells
Public LoadCell(4)
'Logger reference temp for Thermocouple measurements
Public RTemp
67 | P a g e
'Type T thermocouples positioned from top of
'plant mass to bottom of soil layer
Public Temp_C(2)
Units BattV=Volts
Units Moisture=Volumetric Water content
Units Flux=W/m^2
Units LoadCell=mV
Units RTemp=Deg C
Units Temp_C=Deg C
'Define Data Tables
DataTable(GRTM_CR1000,True,-1)
DataInterval(0,1,min,10)
Sample(1,BattV,FP2)
Sample(1,Moisture,FP2)
Sample(1,Flux,FP2)
Sample(1,LoadCell(1),FP2)
Sample(1,LoadCell(2),FP2)
Sample(1,LoadCell(3),FP2)
Sample(1,LoadCell(4),FP2)
Sample(1,Temp_C(1),FP2)
Sample(1,Temp_C(2),FP2)
'Sample(1,Temp_C(3),FP2)
EndTable
'Main Program
68 | P a g e
BeginProg
Scan(1,min,1,0)
'Default Datalogger Battery Voltage measurement BattV
Battery(BattV)
'Reference Temperature from CR1000 Panel
PanelTemp(RTemp,250)
'ECHO Probe EC-5 measurement VW:
BrHalf(Moisture,1,mV2500,1,1,1,2500,False,10000,_60Hz,3.912,-0.446)
'Generic Single-Ended Voltage measurement for Flux sensor
'Full Bridge measurements FullBR() for all 4 LoadCell sensors
BrFull(LoadCell(1),1,mV25,5,2,1,2500,True,True,0,_60Hz,11.7951001,-1.66)
BrFull(LoadCell(2),1,mV25,6,2,1,2500,True,True,0,_60Hz,12.215673,-3.15)
BrFull(LoadCell(3),1,mV25,7,2,1,2500,True,True,0,_60Hz,11.2247555,-3.17)
BrFull(LoadCell(4),1,mV25,8,2,1,2500,True,True,0,_60Hz,11.8252351,-1.22)
Voltdiff(Flux,1,mV25C,2,True,200,250,16.36661,0)
'Type T (copper-constantan) Thermocouple measurements Temp_C()
TCDiff(Temp_C(),2,AutoRange,3,TypeT,RTemp,True,0,_60Hz,1,0)
'Call Data Tables and Store Data
CallTable(GRTM_CR1000)
NextScan
EndProg
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Appendix 5:
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Introduction:
CH2M Hill Center, a 10 story commercial building located at 2020 SW 4th Ave in Portland
Oregon, has atraditional impermeable rock ballast roof system. The roof system is 25 years old
and near the end of its working life. The traditional roof facilitates storm water runoff
contribute to building operations cost and overflow of the Portland metro sewer/storm water
infrastructure because of the large surface area the building covers. Additionally, the low
reflectivity and high emissivity of the rock ballast roof directly contributes to temperatures up
to 50°F greater than ambient air on the roof. Elevated temperatures and direct solar radiation
combine to degrade roof performance, resulting in higher operating and maintenance costs.
Green/Eco roofs are roof systems founded on a reinforced roof structure with the addition of
awaterproof membrane, additionalinsulation, adrainage layer, aroot barrier, soil and plants.
The teams’ goal is to design a green roof system and instrumentation module that will quantify
the impact of design optimizations such as R-Value, evapotransporation, and water retention.
Data collected will assist in making roof replacement recommendations to CH2M Hill
management and provide input for CH2M Hill to produce aCFD model of the proposed
replacement green roof.
Purpose of this Document:
This report is a reference for the design and performance criteria set forth by the
customers. The PDS defines stakeholders, outlines a design project plan and the design team’s
intention. Design requirements, engineering metrics, targets and evaluation methods are
identified and prioritized.
Mission:
The Green Roof team will design and construct a scale green roof and green roof
instrumentation system structurally, tailored for CH2M Hill Center’s 5th floor terrace to meet
thermal and hydrological design criteria. The design will require a green roof test bed that
meets terrace structural load limit and municipal code and a portable instrumentation package.
The design will be documented by a report that contains details of targets, analysis methods,
material selection, instrument selection, as well as drawings and economic analysis of
theproposed replacement roof.
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Top Level Project Plan:
The project plan describes the capstone team’s high priority items and project deadlines.
Item
Start Date
Due Date
Initial Brainstorming
23-Nov
15-Jan
Research Possible Solutions
30-Nov
5-Jan
Initial Design
6-Jan
29-Jan
PDS Report
6-Jan
8-Feb
PDS Presentation
6-Jan
8-Feb
Design Evaluation
29-Jan
22-Feb
Design Final
22-Feb
26-Feb
External/Internal Search Concept Evaluation Presentation
6-Jan
22-Feb
End of Term Progress Report
15-Jan
8-Mar
End of Term Progress Presentation
15-Jan
8-Mar
Prototype and Test
1-Mar
19-Mar
Design Evaluation
15-Mar
17-Mar
Re-Prototype and Test
17-Mar
25-Mar
Assemble
22-Mar
5-Apr
5-Apr
26-Apr
Install
Table 1: List of project milestones with start and due dates.
Identification of Customers:
The primary customers are CH2M Hill as well as Oregon Pacific Development Company
(OPDC, current building owners) as we are designing the green roof test bed for use on their
roof. Other customers include City of Portland and Portland State University (PSU).
Internal customers are PSU, CH2MHill, and OPDC; whereas all other customers would be
considered external.
Customer Feedback:
CH2M Hill is interested in supporting the students at PSU in their project, as well as
hopefully attaining a successful greenroof when the old ballast roof on the building is replaced.
OPDC is mostly interested in dollars and cents and would like to choose the most costeffective method for roof-replacement. They have specified desirables such as a cost of $5 per
square foot of roof replaced and a 5 year payback if the cost is higher.
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City of Portland is concerned with the usability of the instrumentation system and how
it may be integrated with other existing green roofs for mobile monitoring, or how it may be
used to track down possible savings for greenroof prospects.
PSU would like its students to create products that meet the needs of their customers
based and follow the project design rubric. This should ensure product implementation in the
real-world applications they were designed for and create a strong foundation for students to
build on.
All customers would like to see the green roof test bed meet or exceed all current
standards for water quality/retention, temperature reduction, etc. and have the
instrumentation package be a mobile and effective way for tracking the effectiveness of green
roof systems.
Project Design Specifications:
There are several categories of specifications: Performance, Legal, Aesthetics, and
Instrumentation.
Legal will go over the requirements for the green roof to meet city structural and
environmental laws.
 Building Codes – Before installation the plans for the installation of a green roof test
bed must meet applicable city, state, and federal codes and standards.
o Weight – Structural limits on existing roof will drive the weight of the new
roof, would like to keep green roof weight under 15psf.
o Safety – Waterproof membrane must be free of leaks to prevent structure
degradation.
 Documentation – All calculations will be kept for the structural analysis,
performance criteria, and project management aspects.
Performance covers aspects we would like the green roof to achieve so it has a payback
timetable which meets customer needs, as well as provides more benefit to the environment.
 Water Retention – Annual water runoff was reduced by 54% according to our
calculations.
 Temperature Reduction – Reduce rooftop temperature to no more than 10 degrees
Fahrenheit above ambient during CDD (Cooling Degree Days).
 Maintenance – With the inclusion of Rye Grass there may be monthly maintenance
need
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

Durability – The Green Roof test bed should last 20 years, be able to withstand
heavy wind/rain, many hot/cold cycles, and be immune to solar degradation.
Portability – Must be able to be moved with no more than 2 people and fit through a
standard doorway.
Aesthetics requirements for marketing and visual appeal were met as throughout the teams
visits to the site visitors would comment on the design and its visual appeal of a positive nature.
From a marketing standpoint the elementary school provided much better exposure for the
sponsors because of public accessibility and the visual aide describing the project and its
sponsors in front.
 Marketing – Space must create a desirable location through an improved outdoor
experience.
o Visual Appeal –Be a visually stimulating view to uplift workers and create a
sense of appreciation for the workplace.
Instrumentation includes the requirements for the components we would like to use to
monitor the performance of the green roof test bed and any future green roofs that may be
monitored with this instrumentation package.
 Cost – Budget was not exceeded and instrumentation quality has not been an issue.
 Installation – Setup may be completed within one hour and site-specific calibrations
are minimal.
 Compatibility – The system uses three different types of loggers which could have
been simplified to fewer loggers, but the data download is straightforward and can
be completed in just a few minutes.
 Resolution – Was not an issue.
 Durability – Test module has stood up to multiple hard rain cycles without wear
issues and data loggers are insulated and protected by foam on all sides when the
case is closed.
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House of Quality:
Each section within the product design specification section (Performance, Legal, etc.)
has a section within the House of Quality which outlines the main aspects of each section.
Legal
Priority
Customer
Metric
Targets
Basis
Verification
Building Codes
10
All
Location,
Weight, Waterresistance, etc.
Compliant
Govt. Codes
and Standards
Structural
Engineer
Approval
Weight
10
All
lbs/sqft
Allowed
Less than 15psf
Roof Load
Characteristics
Safety
8
All
Roof Leakage
No Leaks
Customer
Feedback
Records for all
Procedures
Requirements
set by
City/State
Documentation
10
All
Records
Required
Instrumentation
Priority
Customer
Metric
Targets
Cost
7
PSU /
CH2MHill
OPDC
Dollars and
Cents
Within Budget
Installation
9
All
Time
Less than 1
Hour to Install
All
Graded Scale 15, 1 being not
compatible, 5
being fully
compatible
5
All
Depends on
Data to be
Measured
All
Operating
Temperature
Range and
Impact
Resistance
Compatibility
Resolution
Durability
8
10
7
Adequate for
Meaningful
Data (Depends
on Instrument)
Within -20 to
120°F and able
to withstand
impact loading
on the order of
10lbs
Structural
Engineer
Approval
Roof
Monitoring and
Customer
Feedback
City Approval
Basis
Funds Promised
by CH2MHill
and OPDC
($5000)
Customer
Feedback on
Need for a
Portable Test
Module
Verification
Balance Sheet
Field Tests
Customer
Needs
Lab and Field
Tests
Performance
Requirements
Lab and Insitu
Data Collection
Measurement
Conditions
Manufacturer
Specifications
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Performance
Water Retention
Temperature
Reduction
Maintenance
Durability
Mobility
Aesthetics
Priority
9
9
6
8
9
Priority
Customer
Metric
Targets
Basis
City of Portland
Averages for
Green Roof
Water
Retention
Verification
All
Avg. Reduction
of Runoff per
Month/Year
60% Annual
Reduction
All
Temperature
on Peak CDD
10°C Above
Ambient Peak
CDD
Performance
Optimization
Modeling,
Field/Experimental
Data Collection
All
Cost of Annual
Upkeep
Equal to or Less
than past
maintenance
costs
Customer
Feedback
Historic Data
Comparison
All
Solar Exposure
and Rapid
Temperature
Change
Immune within
-20 to 120 °F
Construction
Material
Properties
Data Collection
All
Ease of
Transport
Can be moved
without special
equipment
Customer
Feedback
Survey of Users
Data Collection
Customer
Metric
Targets
Basis
Verification
100% Increase
Customer
Feedback
Publications
10
Customer
Feedback
Survey of
Tenants
Marketing
8
All
Approx. %
Increase in
Publicity
Visual Appeal
6
All
Graded Scale 110
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Conclusion/Summary:
The Green Roof Project has been well defined by the above criteria to meet the
needs of CH2M Hill, OPDC, City of Portland, and PSU. The selections of soil, plants,
trays, and instruments will be chosen to meet these specifications. It is the hope of the
team that this project will shine light on the benefits of a well-designed green roof
system and instrumentation package, enough so CH2M Hill and OPDC decide to utilize
these systems on their current building.
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