ARM TR-063

> Soil Water and Temperature System (SWATS) Handbook
>
> January 2005
>
> D. Bond
>
> Work supported by the U.S. Department of Energy,
>
> Office of Science, Office of Biological and Environmental Research

# Contents {#contents .Heading-Front}

[1. General Overview 1](#general-overview)

[2. Contacts 1](#contacts)

[3. Deployment Locations and History
1](#deployment-locations-and-history)

[4. Near-Real-Time Data Plots 1](#near-real-time-data-plots)

[5. Data Description and Examples 1](#data-description-and-examples)

[6. Data Quality 1](#data-quality)

[7. Instrument Details 1](#instrument-details)

**Figures**

[Figure 1. 1](#__RefHeading___Toc94519841)

[Figure 2. 1](#__RefHeading___Toc94519842)

[Figure 3. 1](#__RefHeading___Toc94519843)

[Figure 4. 1](#__RefHeading___Toc94519844)

[Figure 5. 1](#__RefHeading___Toc94519845)

[Figure 6. 1](#__RefHeading___Toc94519846)

**Tables**

[Table 1. 1](#OLE_LINK2)

[Table 2. 1](#__RefHeading___Toc94519848)

[Table 3. 1](#__RefHeading___Toc94519849)

# General Overview

The soil water and temperature system (SWATS) provides vertical profiles
of soil temperature, soil-water potential, and soil moisture as a
function of depth below the ground surface at hourly intervals. The
temperature profiles are measured directly by *in situ* sensors at the
Central Facility and many of the extended facilities of the SGP climate
research site. The soil-water potential and soil moisture profiles are
derived from measurements of soil temperature rise in response to small
inputs of heat. Atmospheric scientists use the data in climate models to
determine boundary conditions and to estimate the surface energy flux.
The data are also useful to hydrologists, soil scientists, and
agricultural scientists for determining the state of the soil.

# Contacts

## Mentor

Don Bond

University of Oklahoma -- CIMMS

100 E. Boyd, Rm 1110

Norman, OK 73019-1011

Phone: (405) 325-2589

<dbond@ou.edu>

## Instrument Developer

Campbell Scientific, Inc.

815 W. 1800 North

Logan, UT 84321-1784

Phone: (435) 753-2342

<info@campbellsci.com>

# Deployment Locations and History 

Current health and status information for each SWATS instrument can be
found at the [DQ HandS](http://dq.arm.gov/) website.

Table 1 identifies the location of the SWATS instrument systems and the
depths at which sensors were installed at each site:

[]{#OLE_LINK2 .anchor}

Table 1.

  ------------------ --------------------------- ------------------------
  **Site Location**  **Depths (cm)**             **Status**

  E1  Larned, KS     5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E2  Hillsboro, KS  5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E3  LeRoy, KS      5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E4  Plevna, KS     5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E5  Halstead, KS   5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  **Table 1.**                                   
  (cont'd)                                       

  **Site Location**  **Depths (cm)**             **Status**

  E6  Towanda, KS    5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E7  Elk Falls, KS  5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E8  Coldwater, KS  5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E9  Ashton, KS     5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E10 Tyro, KS       5, 15, 25, 35, 60           Operating

  E11 Byron, OK      5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E12 Pawhuska, OK   5, 15, 25, 35, 60           Operating

  E13 Lamont, OK     5, 15, 25, 35, 60, 85       Operating

  E15 Ringwood, OK   5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E16 Vici, OK       5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E18 Morris, OK     5, 15, 25, 35, 60, 85, 125, Offline pending
                     175                         reinstallation

  E19 El Reno, OK    5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E20 Meeker, OK     5, 15, 25, 35, 60, 85, 125  Operating

  E22 Cordell, OK    5, 15, 25, 35, 60, 85, 125, Operating
                     175                         

  E24 Cyril, OK      5, 15, 25, 35, 60, 85, 125  Operating

  E25 Seminole, OK   5, 15, 25, 35, 60, 85, 125, Offline (facility
                     175                         removed)

  E27 (Earlsboro)    Tbd                         Offline (facility
                                                 removed)
  ------------------ --------------------------- ------------------------

# Near-Real-Time Data Plots

See the SGP Quick Looks in the Educational Data Plot Library at
<http://education.arm.gov/nsdl/Visualization/quicklook_interface.shtml>

[Data Quality Health and Status
Explorer](http://dq.arm.gov/cgi-bin/dqmenu.pl) Select 'ARM site: SGP'
and 'Data Streams: sgpswats'

[NCVweb](http://dq.arm.gov/ncvweb/ncvweb.cgi) Select 'sgp' then
'sgpswatsExx.b1'

[Plot Browser](http://dq.arm.gov/plotbrowser/) Select 'Search Site -
SGP' and 'Datastream - sgpswats'

# Data Description and Examples

Plots of [Reference
Temperature](http://www.arm.gov/instruments/images/swats/swats_tref.gif),
[Soil
Temperature](http://www.arm.gov/instruments/images/swats/swats_ts.gif),
[Sensor Temperature
Rise](http://www.arm.gov/instruments/images/swats/swats_tr.gif), [Soil
Water
Potential](http://www.arm.gov/instruments/images/swats/swats_swp.gif),
and [Volumetric Water
Content](http://www.arm.gov/instruments/images/swats/swats_wc.gif) after
a precipitation event. [DQ HandS](http://dq.arm.gov/)

## Data File Contents

### Primary Variables and Expected Uncertainty

The system is designed to provide information related to temperature and
moisture in the soil profile. The information provided consists of soil
temperature, soil-water potential, and volumetric water content. Brief
descriptions of these variables, as well as the units of measure, are
given below.

**Soil Temperature:** Soil temperature is the temperature of the
sensor/soil water system. Soil temperature is reported in units of
degrees Celsius (C).

**Soil-Water Potential:** Soil-water potential is a measure of the
energy state of water in the soil. It can be thought of as the tension
with which water is held onto the soil particles, or alternatively, as
the amount of work required to remove the water adsorbed to the soil
particles. Potential is useful in determining such things as the
availability of water for plant uptake, the movement of water within the
soil profile, and evaporation of water from the soil surface. Soil-water
potential is reported in units of kilopascals (kPa).

**Volumetric Water Content:** Volumetric water content is the volume of
water contained in a given volume of soil.  It can be expressed as a
depth of water in a given depth of soil by assuming that soil and water
are homogeneous over a given surface area. Water content is reported in
units of cubic meters of water per cubic meters of soil (m^3^/m^3^),
equivalent to a depth of water per depth of soil (m/m).

**Tsoil:** A direct measurement of the soil temperature

**Soilwatpot:** Soil-water potential, also known as 'matric potential,'
the binding tension between the soil and water (energy required to
remove the water from the soil particles)

**Soilwatcont:** Volumetric water content, the volume of water in a
given volume of soil (depth of water in a given depth of soil); water
content is determined from soil-water potential based on laboratory
studies using soil samples from each location

[]{#__RefHeading___Toc94519848 .anchor}Table 2.

+-------------------+-----------------+-----------+------------------+
| **Data File       | **Variable      | **Units** | **Uncertainty**  |
| Variable**        | Name**          |           |                  |
+-------------------+-----------------+-----------+------------------+
| tsoil_W           | soil            | °C        | 0.5°C            |
|                   | temperature     |           |                  |
| tsoil_E           |                 |           |                  |
+-------------------+-----------------+-----------+------------------+
| soilwatpot_W      | soil-water      | kPa       | 4 -- 20 kPa      |
|                   | potential       |           |                  |
| soilwatpot_E      |                 |           |                  |
+-------------------+-----------------+-----------+------------------+
| soilwatcont_W     | water content   | m^3^/m^3^ | 0.05 m^3^/m^3^   |
|                   |                 |           |                  |
| soilwatcont_E     |                 |           |                  |
+-------------------+-----------------+-----------+------------------+

#### Definition of Uncertainty

We define uncertainty as the range of probable maximum deviation of a
measured value from the true value within a 95% confidence interval.
Given a bias (mean) error B and uncorrelated random errors characterized
by a variance σ^2^, the root-mean-square error (RMSE) is defined as the
vector sum of these,

![](media/image1.wmf){width="1.4027777777777777in"
height="0.3055555555555556in"}.

(B may be generalized to be the sum of the various contributors to the
bias and σ^2^ the sum of the variances of the contributors to the random
errors). To determine the 95% confidence interval we use the Student's t
distribution: tn;0.025 ≈ 2, assuming the RMSE was computed for a
reasonably large ensemble. Then the uncertainty is calculated as twice
the RMSE.

### Secondary/Underlying Variables

tref: the temperature of the internal reference thermistor

trise_W, trise_E: the temperature rise measured by each sensor and
converted to soil-water potential based on laboratory sensor
calibrations

### Diagnostic Variables

serial_numbers_W, serial_numbers_E: serial numbers used to identify
individual soil sensors

### Data Quality Flags

-9999 in the data stream means either that particular sensor depth was
not installed or the data for that sensor is reporting missing.

Additional information may be found at [SWATS Data Object Design
Changes](http://science.arm.gov/tool/dod/showdod.php?Inst=swats) for ARM
netCDF file header descriptions.

Flag=0: value is within the specified range

Flag=1: value is missing (recorded as '-9999')

Flag=2: value is less than acceptable minimum

Flag=4: value is greater than acceptable maximum

Flag=8: failed delta check (value differs too greatly from previous
value)

Data quality flags are used to alert users of bad or questionable data.

For example, the qc variable 'qc_trise_W' is actually a diagnostic
variable equal to the sum of the data quality flags for the variable
'trise_W.' (There are qc variables for the 'tref,' 'tsoil,' 'trise,'
'soilwatpot,' and 'soilwatcont' variables.)

qc_trise_W = 5

To interpret the qc variable, convert the number to base 2. For example,
5 = 4x1 + 0x2 + 1x1 = 101 \[base2\].

qc_trise_W = 4 + 1

This means that the qc variable contains the maximum and missing flags.

trise_W = '-9999' \> acceptable minimum value

[]{#__RefHeading___Toc94519849 .anchor}Table 3.

+--------------+-------------------+--------------+------------------+
| **Variable** | **Acceptable**    | **           | **Acceptable**   |
|              |                   | Acceptable** |                  |
|              | **Minimum**       |              | **Delta**        |
|              |                   | **Maximum**  |                  |
+==============+===================+==============+==================+
| tref         | -25°C             | 50°C         | 20°C             |
+--------------+-------------------+--------------+------------------+
| tsoil        | -20°C             | 50°C         | 20°C             |
+--------------+-------------------+--------------+------------------+
| trise        | 1                 | 4.5          | 3.5              |
+--------------+-------------------+--------------+------------------+
| soilwatpot   | -7000 kPa         | 0 kPa        | 7000 kPa         |
+--------------+-------------------+--------------+------------------+
| soilwatcont  | 0 m^3^/m^3^       | 0.55         | 0.55 m^3^/m^3^   |
|              |                   | m^3^/m^3^    |                  |
+--------------+-------------------+--------------+------------------+

### Dimension Variables

**Time:** a complete file will contain observations for each hour of the
day (dimension 'time' equals 24).

**Depth:** depth (cm) below the surface of the ground (sensor altitude
is equal to the value of 'alt' minus the value of 'depth').

## Annotated Examples

Plots of [Reference
Temperature](http://www.arm.gov/instruments/images/swats/swats_tref.gif),
[Soil
Tempertature](http://www.arm.gov/instruments/images/swats/swats_ts.gif),
[Sensor Temperatue
Rise](http://www.arm.gov/instruments/images/swats/swats_tr.gif), [Soil
Water
Potential](http://www.arm.gov/instruments/images/swats/swats_swp.gif),
and [Volumetric Water
Content](http://www.arm.gov/instruments/images/swats/swats_wc.gif) after
a precipitation event.

Notice how the precipitation (spike seen in the precipitation plot) is
followed by a drop in sensor temperature rise values. This happens
because the added moisture from the rain increases the effective
specific heat of the soil-water system (there is more water in the soil
to heat, thus a smaller rise in temperature). The soil-water potential
values near the surface become less negative (less energy is required to
remove water from wetter soil), and the water content values rise in the
top layers of soil. There is also a more subtle effect (reduction) on
soil temperature.

## User Notes and Known Problems

See [Soil Characterization Studies and Water Retention
Curves](http://www.arm.gov/instruments/publications/OSUSoil/ReadMe.stm).

**Soil and Physical Characteristics of the ARM Extended Facilities with
SWATS.**

The range of soil textures is summarized on a soil texture triangle in
Figure A1. Descriptions and noteworthy details are briefly summarized by
Extended Facility (EF) below.

Soil texture triangle illustrating range of soil textures at the ARM
SWATS sites.

![](media/image2.png){width="4.1097222222222225in"
height="3.941666666666667in"}

[]{#__RefHeading___Toc94519841 .anchor}Figure 1.

*EF1 / LARNED, KS*

Relatively flat site in an area with little relief. No landowner
information concerning whether or not site has ever been plowed; some
indications that it was plowed at some point. There is a wheat field
directly south of the site, with several buildings and a cluster of
trees several hundred meters to the north, and a U.S. highway 1/8 mile
east. Relatively sparse and shallow root layer (density decreased
visibly below \~ 10 cm) under thin short pasture. Very good site from a
micrometeorological point of view.

*EF2 / HILLSBORO, KS*

Broad, relatively shallow slope, southern exposure, in an area with
gently rolling hills. According to landowner, this site has never been
plowed. Substantial sod layer, with roots visible through depth of
access pits (65 cm); pasture more than hip deep in a wet year. Good
micrometeorological site, with clumps of trees several hundred meters to
the east and south.

*EF3 / LE ROY, KS*

Relatively flat site in an area with little relief. No landowner
information concerning whether or not site has ever been plowed.
Extremely dense and deep root layer, easily visible through depth of
access pits; pasture more than hip deep. Very good micrometeorological
site, with a few clumps of trees several hundred meters to the east and
north, soybean field immediately to the south.

*EF4 / PLEVNA, KS*

Relatively flat site in an area with little relief. This is a sandy
site, with thin clumps of vegetation at the surface (bare sand showing
between), and a mix of flat water-smoothed stones. Unlikely that anyone
would have ever plowed this site; few roots, and very little organic
matter. Below about 70 cm, there were occasional bands of clay, but the
layering is discontinuous between the two access pits. Good
micrometeorological site, with significant lines of trees several
hundred meters away in all directions except west.

*EF5 / HALSTEAD, KS*

Relatively flat site in an area with little relief. No landowner
information concerning whether or not site has ever been plowed; some
indication that it was plowed at some point. Medium-density mixed grass
and forb pasture, with roots visible through the depth of the access
pits; winter wheat field to the south. Very good micrometeorological
site, with a few sparse trees several hundred meters away to the north
and west, south of an infrequently traveled gravel road.

*EF6 / TOWANDA, KS*

Seriously disturbed site in a region of irregular hills, with obvious
evidence of terracing in the previous few years; thin layers of
sandstone had been broken and strewn across the pasture in the process.
System was installed on one shelf of the terraced field on a broad slope
with southeast exposure. Soil in the two access holes differed in
texture and color. Medium-density pasture, hip deep, with roots visible
through the depth of the access pits. Previously cultivated field to the
south put into pasture in 1996. Not a good micrometeorological site due
to the terrain variations.

*EF7 / ELK FALLS, KS*

Very flat site in a broad stream valley between irregularly rolling
hills. No landowner information concerning whether or not site has ever
been plowed; mix of good density "improved" pasture suggests that it has
been disturbed to some degree. Roots visible through the depth of the
access pits. Installation occurred after an extended dry period; large
flat fissures, a couple of centimeters wide and tens of centimeters
across, twisted irregularly down through the silt loam and silty clay
soil, intersecting the access pits. Very good micrometeorological site,
with clumps and lines of trees many hundreds of meters away.

*EF8 / COLDWATER, KS*

Relatively flat, sandy site with some gravel, in an area with only
gentle relief. No landowner information concerning whether or not site
has ever been plowed, but some indications that it was plowed at some
time. Vegetation is relatively thin and clumpy, about knee deep, with
bare soil showing. Roots were relatively thin. The hand-augered access
holes (deeper than 85 cm) penetrated into sugar-like sand, pale and
extremely dry. Very good micrometeorological site, with only a few trees
at distance.

*EF9 / ASHTON, KS*

High, broad ridge with expansive view to the north. Pasture appears to
have never been plowed (no landowner confirmation). There is a dramatic
transition in soil texture and color between 60 cm and 85 cm below the
surface that was not included in the soil characterization: soils become
red and clayey, with red and white soft fragmented sandstone beneath
that. Good quality, knee deep, dense mixed grass and forb pasture, with
roots through the depth of the access pits. Micrometeorological data
will be representative of conditions on the broad hilltop.

*EF10 / TYRO, KS*

Site located beside a man-made drainage ditch, with about 50 cm of mixed
fill on top of the original ground level, in a relatively low area
surrounded by higher hills. There is a layer of uneven, lumpy limestone
at 55 cm below the SWATS system, varying as much as 15 cm in depth over
an area 10 m in diameter, broken at the drainage ditch. Vegetation is
hip deep, with roots reaching to the rock layer. The sensors are at 5,
15, 25, 35, and 55 cm, with the 55 cm sensors positioned immediately
adjacent to the rock layer. There is a cultivated field (usually winter
wheat) south of the drainage ditch. Micrometeorological data will be
representative of conditions in the valley.

*EF11 / BYRON, OK*

Very flat site in a wide, low area, with a few dune-shaped small hills
to the far south and east. Proved to be the local low spot: hand
augering hit the water table during installation, with the 125 cm and
175  m sensors installed under water. Since installation, this site has
flooded repeatedly. Relatively dense, knee-deep pasture with roots
visible through the depth of the access pits. Cultivated pasture to the
south, either alfalfa or winter wheat. Very good micrometeorological
site.

*EF12 / PAWHUSKA, OK*

Broad ridge in the [Tallgrass Prairie
Preserve](http://nature.org/wherewework/northamerica/states/oklahoma/preserves/tallgrass.html),
a few hundred meters north of the Oklahoma Mesonet Foraker site
[(http://okmesonet.ocs.ou.edu/)](http://okmesonet.ocs.ou.edu/). The
ground drops sharply several hundred meters north of the EF, and the
pasture has never been plowed. There are irregular rock horizons at this
location, with a broken layer of shale about 45 cm down, and fractured,
increasingly dense sandstone below that. Sensors were installed at 5,
15, 25, 35, and 60 cm. Grazing and fire permitting, the tallgrass can
reach heights of several meters here, and roots were thick down to the
rock. Micrometeorological data will be representative of conditions on
the broad hilltop.

*EF13 / LAMONT, OK (CENTRAL FACILITY)*

Broad hilltop, a few hundred meters west of a valley. The pasture had
been terraced to some degree and \"improved\" several decades
previously, but has returned to a more native mix of grasses and forbs.
Vegetation is greater than hip deep (if ungrazed), and roots were
visible through the depth of the access pits. A layer of sandstone
begins 88 cm below the surface, so sensors are installed at depths of 5,
15, 25, 35, 60, and 85 cm. The original installation in January-February
1996 only included the top five levels due to extremely dry conditions;
the lowest depth (85 cm) was added in February 1997. Micrometeorological
data will be representative of conditions on the broad hilltop.

*EF15 / RINGWOOD, OK*

Sandy site, in a relatively uniform area that appears to be
grass-covered sand dunes, with tree lines several hundred meters to the
north, west, and south. Site appears to have never been plowed (no
landowner confirmation). Soil from the deepest two levels (125 cm and
175 cm) was different in texture, with some clay content. Vegetation is
knee deep and covers the ground more completely than at the other two
sandy sites; roots were visible through the depth of the access pits.
Micrometeorological data will be representative of the area.

*EF16 / VICI, OK*

Relatively flat site, with a slight slope to the north leading to a
tree-filled gully. Wheat field to the south has been terraced, so is
possible that this site was disturbed at some time. Vegetation is knee
deep and tends to be clumpy, with soil occasionally showing between
clumps; roots were visible through the depth of the access pits. Good
micrometeorological site.

*EF18 / MORRIS, OK*

Bermuda hay field, in an extensive area with almost no relief, and a
high water table. The hay field is very flat, with a thick tree line to
the north, good fetch to the south and west, and a busy state highway
due east. During soil sampling and sensor installation, water seeped
down the sides of the sampling trench and access pits. Roots were
visible through the depth of the access pits. Very good
micrometeorological site. The SWATS at this site has suffered repeated
lightning damage.

*EF19/ EL RENO, OK*

Relatively flat site, in gently rolling terrain. Unplowed tallgrass
prairie, with a few buildings several hundred meters to the south.
Grazing and fire permitting, the tallgrass can reach heights of several
meters here, and roots were visible through the depth of the access
pits. Good micrometeorological site. This site is collocated or in
proximity with several other networks: 1.6 km from the Oklahoma Mesonet
El Reno site
[(http://okmesonet.ocs.ou.edu/)](http://okmesonet.ocs.ou.edu/);
co-located with the USDA ARS SHAWMS (site ER01,
[http://grl.ars.usda.gov](http://grl.ars.usda.gov/)); and co-located
with the USDA NRCS National Water & Climate Center's Soil Climate
Analysis Network (site 2022, <http://www.wcc.nrcs.usda.gov/scan/>).

*EF20 / MEEKER, OK*

Broad, north-south ridge in a hilly area, with outcrops of sandstone
along the ridgeline. The field has been plowed at some point. The SWATS
system is located to the west of the ridge, in an area where the first
layer of sandstone is about 130 cm below the surface. There are seven
sensors in each profile at this site, lacking the 175 cm depth. When
ungrazed, vegetation is knee to hip deep; roots were visible through the
depth of the access pits. Micrometeorological data will be
representative of conditions on the ridgeline.

*EF22 / CORDELL, OK*

Gently sloping with southern exposure, in slightly rolling terrain, with
a few trees and buildings several hundred meters to the north, and a
busy U.S. highway to the east. No landowner information available
concerning whether or not the site has ever been plowed. Vegetation is a
knee deep when ungrazed, a bit sparse with bare soil showing between
clumps; roots were visible through the upper half of the access pits.
Good micrometeorological site. Note: the highway is now much closer to
the SWATS than when originally installed, approximately 30 m east of the
system; the rest of the EF has been moved further west.

*EF24 / CYRIL, OK*

Gypsum knoll, with a county road on the north edge, surrounded by wheat
fields. The sensors are located near the southwest edge of the knoll, in
a "hole" in the gypsum filled with soil. The gypsum extends under the
wheat field south of the site for less than 10 m south of the EF, so
soil moisture measurements will probably not be representative of
conditions in the surrounding fields. The installation is non-standard
in sensor placement, but does have two sensors at all depths except
175 cm. Vegetation on the knoll is a mix of cacti and opportunistic
grasses and forbs. Micrometeorological data will be representative of
mixed conditions over the knoll and the surrounding wheat fields.

*EF25 / SEMINOLE, OK*

Relatively flat site, immediately south of a state highway, with tree
lines a few hundred meters in all directions. History of this site is
uncertain, as there is some gravel scattered at the surface, with a
foundry about 1/4 mile south. Soils appeared to be relatively
undisturbed below the topmost 15 cm. Vegetation is relatively dense, and
roots were visible through the depth of the access pits. Not the best
micrometeorological site.

## Frequently Asked Questions

**Q:** (Nov. 18, 2002) How many of the Campbell Model 229L Matric
Potential Sensors are working and how many have died in the SWATS?

**A:** For the 19 SWATS facilities in operation (excluding 1 destroyed
by lightning and 1 being relocated), 270 out of 284 sensors, or 95%, are
still working. 12 sensors are giving bad readings, and 2 are just plain
dead. There is only 1 depth at 1 facility where both sensors are dead
and we don't have data for that soil layer. These sensors have been in
place since 1996/1997.

**Q:** (Nov. 18, 2002) Who does the ingest of the SWATS data?

**A:** ARM's Engineering Group, located at Pacific Northwest National
Laboratory, is in charge of the ingest.

# Data Quality

## Data Quality Health and Status

The following links go to current data quality health and status
results:

-   [DQ HandS](http://dq.arm.gov/) (Data Quality Health and Status)

-   [NCVweb](http://dq.arm.gov/ncvweb/ncvweb.cgi) for interactive data
    plotting using.

The tables and graphs shown contain the techniques used by ARM's data
quality analysts, instrument mentors, and site scientists to monitor and
diagnose data quality.

[Data Quality Health and Status
Explorer](http://dq.arm.gov/cgi-bin/dqmenu.pl) Select 'ARM site: SGP'
and 'Data Streams: sgpswats'

## Data Reviews by Instrument Mentor

Mentor notes on data quality control procedures:

-   **QC frequency**: Once per week

-   **QC delay**:

-   **QC type**: Graphical plots, data quality metric tables

-   **Inputs**: Netcdf data plots

-   **Outputs**: data quality reports (DQRs) issued to the site
    scientist team

-   **Reference**:

Data QC procedures for this system are continually being developed.

The instrument mentor inspects SWATS data from all sites at least once
per week. The mentor reports data deficiencies via DQRs to the SGP site
scientist team and continually works with Site Operations to issue work
orders to fix any problems noted.

The mentor uses several means to inspect the data. Inspection of plots
and data quality metric tables at the SGP SST Web site to look for
obvious problems and to identify the approximate times of problems.

## Data Assessments by Site Scientist/Data Quality Office

All Data Quality (DQ) Office and most Site Scientist techniques for
checking have been incorporated within [DQ HandS](http://dq.arm.gov/)
and can be viewed there.

Assessments of the SWATS precipitation measurements (supplementary
tipping bucket raingauge data at selected facilities are included in the
[Data Quality Office's Weekly Data Quality Assessments
summaries](http://www.dq.arm.gov/weekly_reports/weekly_reports.html).)

## Value-Added Procedures and Quality Measurement Experiments

Many of the scientific needs of the ARM Program are met through the
analysis and processing of existing data products into "value-added"
products or VAPs. Despite extensive instrumentation deployed at the ARM
sites, there will always be quantities of interest that are either
impractical or impossible to measure directly or routinely. Physical
models using ARM instrument data as inputs are implemented as VAPs and
can help fill some of the unmet measurement needs of the program.
Conversely, ARM produces some VAPs not to fill unmet measurement needs,
but to improve the quality of existing measurements. In addition, when
more than one measurement is available, ARM also produces "best
estimate" VAPs. A special class of VAP, called a Quality Measurement
Experiment (QME), does not output geophysical parameters of scientific
interest. Rather, a QME adds value to the input datastreams by providing
for continuous assessment of the quality of the input data based on
internal consistency checks, comparisons between independent similar
measurements, or comparisons between measurement with modeled results,
and so forth. For more information, see the [VAPs and
QMEs](http://www.arm.gov/data/vaps.stm) web page.

# Instrument Details

## Detailed Description

### List of Components

The system consists of several components that enable the system to
collect, store, and transmit data automatically. All of the components,
with the exception of the sensors, are installed in a weatherproof
enclosure located above the soil surface. The components of the system
include the following:

-   Sensor

```{=html}
<!-- -->
```
-   Model 229L Matric Potential Sensor, Campbell Scientific, Inc.

```{=html}
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```
-   Datalogger

```{=html}
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```
-   Manages measurement and control functions

-   Campbell Scientific, Inc. Models CR10 and CR10x.

```{=html}
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```
-   Multiplexer

    -   Allows the connection of up to 16 sensors

    -   Campbell Scientific, Inc. Model AM416.

-   Constant-current source

```{=html}
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```
-   Provides a regulated current for driving the sensor resistance
    heater

-   Campbell Scientific, Inc. Model CE8.

```{=html}
<!-- -->
```
-   Power supply

```{=html}
<!-- -->
```
-   Provides electrical power for the datalogger and telecommunications
    equipment

-   Campbell Scientific, Inc. Model PS12.

```{=html}
<!-- -->
```
-   Storage module

```{=html}
<!-- -->
```
-   Allows long-term, back-up data storage

-   Campbell Scientific, Inc. Model SM192.

```{=html}
<!-- -->
```
-   Communications equipment

```{=html}
<!-- -->
```
-   Allows communication with external devices

-   Campbell Scientific, Inc. Model SC32A.

### System Configuration and Measurement Methods

**Sensors**: At a typical SWATS site, sensors are installed at 8
different depths in the soil profile: 5, 15, 25, 35, 60, 85, 125, and
175 cm below the soil surface. Two profiles of sensors are installed at
each site for replication and redundancy of measurements, resulting in a
total of 16 sensors at each site. The two sensor profiles are located
1 m apart from each other. At several of the sites, however, rock or
impermeable soil layers prohibited the installation of sensors at the
greater depths, resulting in less than 8 sensors in each profile.

**Installation**: At each of the sites, all installation work was
performed manually to minimize disturbance of the soil and vegetation at
the site, and to minimize safety hazards. Sensors were placed in soil
that had been disturbed as little as possible. This was accomplished by
minimizing the amount of soil excavated, and by placing the sensors as
far away from the excavated area as possible. This resulted in a
relatively undisturbed profile of soil in which measurements are made.
The electronics enclosure containing the electronic measurement
equipment is mounted on a concrete slab placed on the ground surface to
minimize the influence of the equipment on the SWATS sensors and on
other instrument systems at the site.

The following two figures illustrate the side and top views of a typical
installation with sensors installed at all 8 depths:

Top view of deployment

![](media/image3.png){width="4.25in" height="3.2090277777777776in"}

[]{#__RefHeading___Toc94519842 .anchor}Figure 2.

Side view of deployment.

![](media/image4.png){width="4.209027777777778in"
height="3.495833333333333in"}

[]{#__RefHeading___Toc94519843 .anchor}Figure 3.

Methods of measurements are further described under Section 7.2., Theory
of Operation.

### Specifications

See Section 7.1.1, List of Components for details on the sensors.

[The Campbell Scientific 229L Soil-Water Potential
Sensor](http://www.campbellsci.com/229-l)

## Theory of Operation

The Model 229L Matric Potential Sensor is designed to provide estimates
of matric (or soil-water) potential. The sensor consists of a ceramic
matrix, into which a hypodermic needle has been inserted.  Inside the
hypodermic needle are a thermocouple junction and a resistance heater. A
rigid plastic body attaches the hypodermic needle to the ceramic matrix
and secures the thermocouple and heater wiring. A sketch of the sensor
is shown in Figure 4.

![](media/image5.jpeg){width="4.509722222222222in"
height="4.101388888888889in"}

[]{#__RefHeading___Toc94519844 .anchor}Figure 4.

The sensor operates on a heat-dissipation principle. A heat pulse is
generated by supplying an electrical current for a short time period to
the resistance heater inside the sensor. Heat is dissipated by water
held in the pore spaces. The temperature rise resulting from the heat
pulse and subsequent dissipation of some of the heat is measured with
the thermocouple junction inside the sensor. If the pore spaces contain
much water, a large amount of heat can be dissipated and the temperature
rise will be small. If the pore spaces contain little water and mostly
air, the air acts as an insulator, little heat is dissipated, and a
large temperature rise results.

A calibration curve relates water potential to temperature rise. The
calibration curve returns a water potential value based on the
temperature rise reported by the sensor.

To obtain an estimate of the volumetric water content of the soil, the
water-holding characteristics of the soil must be known. The soil-water
retention curve, also referred to as the water release curve or moisture
characteristic curve, relates the water content to the water potential
of the soil. This relationship is unique for each soil, and is a
function of physical properties, such as soil particle-size
distribution, organic-matter content, and compaction. Knowing this
relationship, an estimate of water content can be made based on a value
of water potential.

The process by which temperature, water potential, and water content
values are obtained is as follows:

1.  Measure the initial sensor/soil temperature with the thermocouple.

2.  Introduce a heat pulse into the sensor by supplying a current to the
    resistance heater for a specified length of time.

3.  Turn off the heating current and measure the heated-sensor
    temperature.

4.  Calculate the sensor temperature rise by subtracting the initial
    temperature from the temperature after heating.

5.  Convert the sensor temperature rise into an estimate of soil water
    potential by applying a sensor calibration function.

6.  Convert the water potential estimate into an estimate of soil water
    content by applying a moisture characteristic function.

Sensor measurements are made and recorded at 1-hour intervals throughout
the day. Each sensor reports the following information at each
measurement interval:

-   initial sensor/soil temperature

-   sensor temperature rise (difference between after-heating and
    initial temperatures)

-   soil-water potential estimate

-   volumetric water content estimate.

All 16 sensors (8 sensors in each of two profiles) at each site are read
within a 6-minute period. Data are stored in the datalogger internal
memory, which will accommodate approximately 3 days of data storage
before any data are overwritten and lost. Data are also stored in the
storage module, which will accommodate approximately 15 days of data
storage before any data are overwritten and lost.

## Calibration

### Theory

The SWATS calibration is sufficiently complicated to justify a brief
review as precursor for this report. Recall that the calibration for the
229-L heat dissipation sensors in the SWATS is a two-step process. The
first step produces a matric potential value ("suction") from the raw
measurement of temperature change over a heating cycle (delta T). This
is related to the amount of work required to move water in the soil,
with units of kPa. The second step produces an estimate of volumetric
water (m^3^/m^3^) from the potential, using the unique soil water
retention curves measured by Oklahoma State University (OSU) for each
soil horizon at all the SWATS sites. This report is in reference to a
proposed change in the first step of this two step process. NO change is
currently recommended for the second step.

After a considerable amount of laboratory work, Ken Fisher issued a
recommendation to revise the matric potential calibration. This
laboratory work has been in the "wet" end of the range of observation to
date, from 0 to about 160 kPa. Dr. Fisher has confirmed that the 229-L
sensors do not respond to changes in water between 0 and about 10 kPa;
i.e., their porous ceramic wick does not begin to drain until the
suction reaches that level. The revised calibration takes this behavior
into account. The first one did not. Due to the improved performance in
very wet conditions, and the simpler form of the calibration equation,
the Oklahoma Mesonet has decided to use this revised calibration for
their 229-Ls. We recommend that ARM follow suit, calling the original
calibration "First-Generation", and the new one "Second-Generation,"
because subsequent revisions may be developed in the future. It is
imperative to maintain the original data during any revision of the
SWATS data in the ARM archive, in particular the soil temperature and
the raw measurement of temperature change over a heating cycle (DeltaT).

The revised calibration ensures proper values of matric potential at the
wet end, but leaves the dry end unresolved at present. The difference in
matric potential between the two calibrations is dramatic as the soils
dry beyond 300 kPa (see Figures 1 and 2). At this point in time, Dr.
Fisher has no definitive data on the behavior of the sensors in the 300
to 2000 kPa range. Published work by Reese on six earlier-model 229-Ls
reported accurate response out to 1200 kPa, so there is reason to
believe that a useful calibration could be developed. Until such work is
performed, we have no definitive means to choose between the two. One of
us (Jeanne Schneider) expects that a "Third-Generation" matric potential
calibration will be shaped like the revised calibration, but closer to
the first generation calibration at the dry end, approaching an
asymptote of about 1500 kPa as the volumetric water approaches the
residual volumetric water for that particular soil.

The impact of the "Second Generation" potential calibration on the
estimate of volumetric water is much smaller, and primarily at the wet
end. Figure 1 gives an example of the impact at two different levels
over a two-month period. During wet conditions in a silt loam soil
(potential \< -50 kPa), the second-generation volumetric water is almost
3% drier. During dry conditions (late July in the plot), the difference
is only about 1%.

If you are unfamiliar with the shape of the relationship between
potential and volumetric water (the soil water release curve), it may
seem irrational that a large change in potential equates to such a small
change in volumetric water. At both the extremely wet and dry ends of
the distribution, small changes in volumetric water content produce huge
changes in potential. The dynamic response range for a soil (where one
can differentiate drying from either dry or wet) is usually between
about 5 kPa and 500 kPa. \[There is an exception: sand or loamy sand
soils tend to be either dry or wet, changing rapidly between the two
states; in these sandy soils, there is no useful dynamic response range
for relating potential and volumetric water. Further, the 229-L's do NOT
respond to wetting and drying in a manner similar to the sand. The
sensors wet more slowly and only partially, and then retain water long
after the sand has dried. This is why the SWATS soil water data at EFs
4, 8, and15 will never be representative of the soil state.\]

In summary:

we have an improved calibration available for the matric potential in
the wet end of the range of observations;

calibrations issues remain for the dry end of the range of observations;

Adjustment of individual sensor response to

["reference" sensor response (NO CHANGE)]{.underline}

![](media/image6.png){width="3.2631944444444443in"
height="0.2604166666666667in"}

Removes sensor-to-sensor variability; coefficients m and b are unique
for each individual sensor.

Where

dT~ref~ = "reference" sensor response ( C )

dT~sensor~ = individual sensor response ( C )

m = slope b = intercept\
 

"Reference" Sensor Calibration Equation

\*\*\*\*\*\*\*\*\*\*\*FIRST-GENERATION CALIBRATION\*\*\*\*\*\*\*\*\*\*

Estimates potential as a function of reference sensor response;
coefficients dT~d~, dT~w~, a, n are constant for all sensors.

![](media/image7.png){width="4.375694444444444in"
height="1.1305555555555555in"}

Where

Ψ = potential (kPa)

dT~d~ = 4.00 ( C ) dT~w~ = 1.45 ( C )

a = -0.01 (kPa) n = 0.77\
   

\*\*\*\*\*\*\*\*\*\*\*SECOND GENERATION
CALIBRATION\*\*\*\*\*\*\*\*\*\*\*

![](media/image8.png){width="2.3020833333333335in" height="0.40625in"}

Where

a = 1.788

c = 0.717\
 

Soil Water Retention Curve (NO CHANGE)

![](media/image9.png){width="4.363194444444445in"
height="1.6083333333333334in"}

Estimates water content as a function of potential; coefficients Q~r,~
Q~s,~ a, n are unique for each different soil layer at each site.

Where

Θ = volumetric soil water content ( m^3^ / m^3^ )

Θ~r~ = residual water content ( m^3^ / m^3^ )

Θ~s~ = saturated water content ( m^3^ / m^3^ )

**α**, n = empirical constants Ψ  =potential (kPa)\
   

Volumetric Water Contnet for Both First- and Second-Generation
Calibration Technique

![](media/image10.png){width="5.622222222222222in" height="3.5875in"}

[]{#__RefHeading___Toc94519845 .anchor}Figure 5.

Matric Potential (Soil Water Potential) for Both First- and
Second-Generation Calibration Technique

![](media/image11.png){width="5.625in" height="3.365972222222222in"}

[]{#__RefHeading___Toc94519846 .anchor}Figure 6.

### Procedures

**Sensor Calibration**

The sensors were calibrated to yield a soil-water potential value in
response to a temperature rise in the sensor. The resulting calibration
equation gives soil water potential as a function of sensor temperature
rise.

Early analysis of sensor performance indicated that response varied from
sensor to sensor, but that the shape of the response curves was similar
for all sensors. Two points on each sensor curve, when the sensor was
wet and when the sensor was completely dry, were used to reduce the
sensor-to-sensor variability. Linear regression was used to adjust the
response of each sensor to that of a "reference" sensor.

The method used in calibrating the 229L sensor involved correlating
measurements of potential made with thermocouple psychrometers to
temperature-rise readings made with the 229L sensor. A set of 229L
sensors and thermocouple psychrometers were placed together in a soil
container. The soil was initally saturated and allowed to slowly dry.
Readings were taken concurrently from the thermocouple psychrometers and
the 229L sensors as the soil dried. A calibration equation was then
developed from the concurrent readings.

**Soil Analyses**

A number of physical analyses for the soils at each of the ARM EFs were
performed by the Oklahoma State University Biosystems and Agricultural
Engineering Department. At each site, a trench was dug 0.5 m deep to
visually characterize the soil profile and to identify different soil
layers. Multiple soil samples were collected from each distinct soil
layer, and were returned to the laboratory for analysis. The samples
were analyzed to determine: a) the particle-size distribution; b) sand,
silt, and clay fractions; c) textural classification; d) organic-matter
content (in the near-surface layer only); and e) the soil-water
retention curve.

The soil water retention curves allow estimates of volumetric water
content to be made based on water potential values obtained from the
229L sensors. The van Genuchten form of the water content vs potential
equation was fit to the water retention laboratory data from each soil
layer, resulting in unique relationships for each soil layer at each
site.

### History

Comparisons of the water content estimates made with the 229L sensors
involves comparing sensor estimates to estimates or measurements of
water content made independently of the 229L sensors.  Independent water
content estimates may be determined from gravimetric analysis of soil
samples collected at each site, or from water content measurements made
with neutron meters or TDR instruments. This work is ongoing, with work
being performed by the OSU Biosystems and Agricultural Engineering
Department and the Oklahoma Climatological Survey located at the
University of Oklahoma.

24 July 2001

[Latest Report on SWATS
Calibrations](http://www.arm.gov/instruments/publications/swats_mesonet.pdf)\
\
26 July 2000

Status Report on SWATS Calibrations

Jeanne M. Schneider, Ken Fisher and Chad Bahrmann

The SWATS calibration is sufficiently complicated to justify a brief
review as precursor for this report. Recall that the calibration for the
229-L heat dissipation sensors in the SWATS is a two-step process. The
first step produces a matric potential value ("suction") from the raw
measurement of temperature change over a heating cycle (delta T). This
is related to the amount of work required to move water in the soil,
with units of kPa. The second step produces an estimate of volumetric
water (m^3^/m^3^) from the potential, using the unique soil water
retention curves measured by OSU for each soil horizon at all the SWATS
sites. This report is in reference to a proposed change in the first
step of this two step process. No change is currently recommended for
the second step.

After a considerable amount of laboratory work, Ken Fisher issued a
recommendation to revise the matric potential calibration. This
laboratory work has been in the "wet" end of the range of observation to
date, from 0 to about 160 kPa. Dr. Fisher has confirmed that the 229-L
sensors do not respond to changes in water between 0 and about 10 kPa;
i.e., their porous ceramic wick does not begin to drain until the
suction reaches that level. The revised calibration takes this behavior
into account. The first one did not. Due to the improved performance in
very wet conditions, and the simpler form of the calibration equation,
the Oklahoma Mesonet has decided to use this revised calibration for
their 229-Ls. We recommend that ARM follow suit, calling the original
calibration "First Generation," and the new one "Second Generation,"
because subsequent revisions may be developed in the future. It is
imperative to maintain the original data during any revision of the
SWATS data in the ARM archive, in particular the soil temperature and
the raw measurement of temperature change over a heating cycle (DeltaT).

The revised calibration ensures proper values of matric potential at the
wet end, but leaves the dry end unresolved at present. The difference in
matric potential between the two calibrations is dramatic as the soils
dry beyond 300 kPa (see Figures 1 and 2). At this point in time, Dr.
Fisher has no definitive data on the behavior of the sensors in the 300
to ?2000 kPa range. Published work by Reese on six earlier-model 229-Ls
reported accurate response out to 1200 kPa, so there is reason to
believe that a useful calibration could be developed. Until such work is
performed, we have no definitive means to choose between the two. One of
us (Jeanne Schneider) expects that a "Third Generation" matric potential
calibration will be shaped like the revised calibration, but closer to
the first generation calibration at the dry end, approaching an
asymptote of about 1500 kPa as the volumetric water approaches the
residual volumetric water for that particular soil.

The impact of the "Second Generation" potential calibration on the
estimate of volumetric water is much smaller, and primarily at the wet
end. Figure 1 gives an example of the impact at two different levels
over a two-month period. During wet conditions in a silt loam soil
(potential \< -50 kPa), the second generation volumetric water is almost
3% drier. During dry conditions (late July in the plot), the difference
is only about 1%.

If you are unfamiliar with the shape of the relationship between
potential and volumetric water (the soil water release curve), it may
seem irrational that a large change in potential equates to such a small
change in volumetric water. At both the extremely wet and dry ends of
the distribution, small changes in volumetric water content produce huge
changes in potential. The dynamic response range for a soil (where one
can differentiate drying from either dry or wet) is usually between
about 5 kPa and 500 kPa. \[There is an exception: sand or loamy sand
soils tend to be either dry or wet, changing rapidly between the two
states; in these sandy soils, there is no useful dynamic response range
for relating potential and volumetric water. Further, the 229-L's do NOT
respond to wetting and drying in a manner similar to the sand. The
sensors wet more slowly and only partially, and then retain water long
after the sand has dried. This is why the SWATS soil water data at EFs
4, 8, and15 will never be representative of the soil state.\]

In summary:

-   we have an improved calibration available for the matric potential
    in the wet end of the range of observations

-   calibrations issues remain for the dry end of the range of
    observations.

## Operation and Maintenance

### User Manual

Please contact the mentor (Section 2.1) for a copy of the SWATS User
Manual.

### Routine and Corrective Maintenance Documentation

[Preventative Maintenance
Procedures](http://www.ops.sgp.arm.gov/pm_proc/swatspm.htm)

Corrective maintenance generally entails reconfiguring the wiring in the
above-ground electronics box and/or replacing electronics components as
deemed necessary during troubleshooting. Corrective maintenance
documentation is in draft form -- please contact the mentor (See Section
2.1) to obtain documentation.

### Software Documentation

ARM netCDF file header descriptions may be found at [SWATS Data Object
Design Changes](http://science.arm.gov/tool/dod/showdod.php?Inst=swats).

### Additional Documentation

See the [Preventative Maintenance Procedure Summaries for the
SWATS](http://www.db.arm.gov/emp-bin/MDS/ListPM.pl?instrument=SWATS) at
the Southern Great Plains (SGP) Site.

[The Campbell Scientific 229L Soil-Water Potential
Sensor](http://www.campbellsci.com/229-l)

## Glossary

Also see the [ARM Glossary](http://www.arm.gov/about/glossary.stm).

## Acronyms

ARM Atmospheric Radiation Measurement (Program)

EF extended facility

OSU Oklahoma State University

RMSE root-mean-square error

SGP Southern Great Plains

SST Site Scientist Team

SWATS soil water and temperature system

USDA U.S. Department of Agriculture

Also see the [ARM Acronyms and
Abbreviations](http://www.arm.gov/about/acronyms.stm).

## Citable References

Spatiotemporal Variations in Soil Water: First Results from the ARM SGP
CART Network

Schneider J. M., D. K. Fisher, R. L. Elliott, G. O. Brown, and C. P.
Bahrmann. J*ournal of Hydrometeorology* 4(1):106-120.