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Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA

Documentation Revision Date: 2016-11-21

Data Set Version: V1

Summary

This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites in four states (California, Arizona, Oklahoma, and Michigan) in the United States. SoilSCAPE used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data at up to 12 sites over varying durations since August 2011. At its maximum, the network consisted of over 200 wireless sensor installations (nodes), with a range of 6 to 27 nodes per site. The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at three to four depths, nominally at 5, 20, and 50 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. Temperature sensors were installed at 5 cm depth at six of the sites. Data collection started in August 2011 and continues at eight sites through late 2016. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional (airborne, e.g. NASA's Airborne Microwave Observation of Subcanopy and Subsurface Mission - AirMOSS) and national (spaceborne, e.g. NASA's Soil Moisture Active Passive - SMAP) scales.

This data set includes 249 files in NetCDF v4 (*.nc) format; 231 node-level 20-min soil moisture data files, 12 site-level files containing the daily average soil moisture, and six soil temperature data files. There are also companion files, consisting of 116 photos of the sensor nodes in the field, and ten maps providing soil and site characteristics for each SoilSCAPE site.

Figure 1. Site-average daily root zone soil moisture for Tonzi Ranch, CA site. Daily precipitation data is shown for comparison (from Daymet, 2016).

Citation

Moghaddam, M., A.R. Silva, D. Clewley, R. Akbar, S.A. Hussaini, J. Whitcomb, R. Devarakonda, R. Shrestha, R.B. Cook, G. Prakash, S.K. Santhana Vannan, and A.G. Boyer. 2016. Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1339

Table of Contents

  1. Data Set Overview
  2. Data Characteristics
  3. Application and Derivation
  4. Quality Assessment
  5. Data Acquisition, Materials, and Methods
  6. Data Access
  7. References
  8. Data Set Revisions

Data Set Overview

This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites in four states (California, Arizona, Oklahoma, and Michigan) in the United States. SoilSCAPE used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data at up to 13 sites over varying durations since August 2011. At its maximum, the network consisted of over 200 wireless sensor installations (nodes), with a range of 6 to 27 nodes per site. The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at three to four depths, nominally at 5, 20, and 50 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. Temperature sensors were installed at 5 cm depth at six of the sites. Data collection started in August 2011 and continues at eight sites through late 2016.

The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional (airborne, e.g. NASA's Airborne Microwave Observation of Subcanopy and Subsurface Mission - AirMOSS) and national (spaceborne, e.g. NASA's Soil Moisture Active Passive - SMAP) scales.

Related Data Sets:

The SoilSCAPE data can be used for validation of soil moisture estimates derived by the AirMOSS project. Access AirMOSS data at ORNL DAAC.

Acknowledgements:

Funding for the SoilSCAPE project came from NASA's Earth Science Technology Office, Advanced Information Systems Technology program.

Data Characteristics

Spatial Coverage: Continental USA

Spatial Resolution: Point locations

Temporal Coverage: The data covers the period 2011-08-03 to 2016-11-14. Sampling is continuing at active sites, and data will be updated periodically.

Temporal Resolution: 20 minutes

Study Area: (all latitudes and longitudes given in decimal degrees)

Site

Westernmost Longitude

Easternmost Longitude

Northernmost Latitude

Southernmost Latitude

Continental USA

-120.99

-83.663

42.299

31.735

 

Table 1. SoilSCAPE Sites. * Inactive sites.

Site

Number of nodes

Temperature Measured

Start Date

End Date

Westernmost Longitude

Easternmost Longitude

Northernmost Latitude

Southernmost Latitude

Kendall, AZ

10

No

2015-08-16

2016-11-14

-109.946

-109.940

31.737

31.735

Lucky Hills, AZ

7

No

2015-08-17

2016-11-14

-110.052

-110.052

31.744

31.742

BLM Land 1 (S Tonzi), CA

17

No

2013-07-05

2016-11-14

-120.906

-120.904

38.393

38.390

BLM Land 2 (S Tonzi), CA

16

No

2013-07-08

2016-11-14

-120.906

-120.904

38.389

38.386

*BLM Land 3 (N Tonzi), CA

6

No

2015-11-02

2016-04-26

-120.994

-120.994

38.471

38.470

New Hogan Lake South, CA

18

Yes

2012-12-13

2016-11-14

-120.789

-120.785

38.150

38.145

New Hogan Lake North, CA

14

Yes

2012-10-18

2016-11-14

-120.806

-120.806

38.173

38.171

*Terra d’ Oro, CA

27

Yes

2013-04-06

2015-10-26

-120.799

-120.794

38.507

38.503

Terra d’ Oro, CA

24

No

2016-01-13

2016-11-14

-120.797

-120.796

38.507

38.504

Tonzi Ranch, CA

19

Yes

2012-08-17

2016-11-14

-120.968

-120.964

38.433

38.430

*Vaira, CA

24

No

2012-09-08

2012-10-19

-120.955

-120.947

38.417

38.412

*Matthaei Gardens, MI

27

No

2011-08-03

2014-06-14

-83.666

-83.663

42.299

42.297

*Canton, OK

21

Yes

2011-08-26

2016-06-11

-98.632

-98.628

36.002

36.000

 

site locations

Figure 2. SoilSCAPE site locations.

 

Data File Information

This data set includes 237 files in NetCDF format for 20-min interval data, 231 for soil moisture and 6 for soil temperature. There are 12 site-specific files for the daily averages of soil moisture. The locations of the sites are provided in Table 1.

 

Table 2. File Naming Convention

File Name

Description

soil_moist_20min_aaa_XX_nNNN.nc

20 min interval soil moisture data (node level files)

soil_temp_20min_aaa_XX_nNNN.nc

20 min interval soil temperature data (node level files)

soil_moist_daily_aaa_XX.nc

Daily average soil moisture data for each node (site level files)

aaa = Name of site (each site contains multiple nodes)

XX = State (e.g. OK, AZ, CA, MI)

NNN = Node ID (physicalid)

 

 

Table 3. Data fields in the 20 min interval soil moisture files (e.g. soil_moist_20min_aaa_XX_nNNN.nc)

Data Field

Units

Description

time

minutes since 2011-01-01

Date and time of the data collection

physicalid

 

Physical identifier of the node

lat

decimal degrees

Latitude of the node

lon

decimal degrees

Longitude of the node

soil_moisture

%

Volumetric soil moisture. Soil moisture values expressed as percentage volumetric water content. To convert to m^3/m^3 divide by 100.

moisture_flag

 

Soil moisture flag. For each sensor there is a numeric flag. The flags are intended to mirror the CEOP Data Flags used by the International Soil Moisture Network.

0 - (G) Good (Standard for all data)

1 - (D) Dubious (Automatically flagged, spikes etc.,)  

2 - (I) Interpolated / Estimated 

3 - (B) Bad (Manually flagged)  

4 - (M) Missing  

5 - (C) Exceeds field size (Negative SM values, fixed at 0.1 percent).

Spikes are detected if |sm[i] - med(sm[i-1:i+1])| > 10 percent. Spikes are set to -9999.0 and flagged using flag 1. Soil moisture values less than 0.1 percent are fixed at 0.1 percent and flagged (5), negative values sometimes occur due to the current calibration. Values over 60 percent are flagged (5) and set to -9999.0.

depth

cm

Depth at which the soil moisture sensors are placed

sensor

 

Type of the soil moisture sensor. This can be either Decagon’s ‘EC-5’ or ‘5TM’ sensor. ‘NA’ means sensor information is not available.

 

Table 4. Data fields in the 20 min interval soil temperature files (e.g. soil_temp_20min_aaa_XX_nNNN.nc)

Data Field

Units

Description

time

minutes since 2011-01-01

Date and time of the data collection

physicalid

 

Physical identifier of the node

lat

decimal degrees

Latitude of the node

lon

decimal degrees

Longitude of the node

soil_temperature

degrees Celsius (C)

Soil temperature. Soil temperature measured with a custom-made probe placed at 5 cm below the soil surface. Accuracy is +/- 0.5 degrees for temperatures in the range 5 - 30 degrees and +/- 1.5 degrees outside this range.

temp_flag

 

Soil temperature flag. Soil temperature outside the range of -30 to 80 degrees C were flagged (5) and the soil temperature values set to -9999.0f.

 

Table 5. Data fields in the daily average soil moisture files (e.g. soil_moist_daily_aaa_XX.nc)

Data Field

Units

Description

time

days since 2011-01-01

Date of the data collection

physicalid

 

Physical identifier of the node

lat

decimal degrees

Latitude of the node

lon

decimal degrees

Longitude of the node

soil_moisture

%

Daily average volumetric soil moisture for a node. Soil moisture values expressed as percentage volumetric water content, to convert to m^3/m^3 divide by 100. Soil moisture values with moisture flag values of 0 (Good) and 2 (Interpolated/Estimated) were used to compute the daily average.

depth

cm

Depths at which the soil moisture sensors were placed

 

Companion Files:

Companion files with this data set include 116 photos of the sensor nodes in the field (compressed within the “NodePhotos” directory), and ten *.pdf maps providing soil and site characteristics for each SoilSCAPE site.

Application and Derivation

This data set can be used for:

(1) Generation of local scale estimates of soil moisture at high temporal resolution. The point measurements from the sensor are scaled up to regional level hydrological models to produce local estimates of soil moisture.

(2) Validation of remote sensing based estimates of soil moisture. Currently, the dataset is being used as part of validation dataset for two NASA missions – Airborne Microwave Observation of Subcanopy and Subsurface Mission (AirMOSS) and spaceborne Soil Moisture Active Passive (SMAP).

Quality Assessment

Uncertainty in the data was not quantified. The data was calibrated using site specific calibration equations and Decagon mineral soil calibration. The standard calibration equation from Decagon used for converting the raw data (voltage * 1024/1200) to volumetric soil moisture (VSM %) is:

VSM = -40.1 + 0.1279569 * raw

For some sites in California, additional soil samples were collected to update the calibration (Table 6). These calibrations had RMSE of 1.5 % compared to the field-collected samples.

Measurement spikes were removed by comparing to the immediately previous and following measurements for the node. The minimum soil moisture is fixed at 0.1 percent. The sensors with very noisy measurements (based on manual checking) were set to -9999.0. The flag values are included in the data file for each sensor.

For temperature (T) calibrations, the raw value is converted to degrees C as:

T = ((1.075268 * raw) - 500) / 10) + 1.8

 

Table 6. Site-specific equations applied to calibrate raw data to volumetric soil moisture (VSM)

Site

Calibration

Kendall, AZ

VSM = -40.1 + 0.1279569 * raw

Lucky Hills, AZ

VSM = -40.1 + 0.1279569 * raw

BLM Land 1 (S Tonzi), CA

VSM = -34.79 + 0.1111 * raw

BLM Land 2 (S Tonzi), CA

VSM = -34.79 + 0.1111 * raw

BLM Land 3 (N Tonzi), CA

VSM = -40.1 + 0.1279569 * raw

New Hogan Lake North, CA

VSM = 9.92249  - 0.133828  * raw + 0.000358248 * raw^2

New Hogan Lake South, CA

VSM = 9.92249  - 0.133828  * raw + 0.000358248 * raw^2

*Terra d’ Oro, CA (2013-2015)

VSM = 9.92249  - 0.133828  * raw + 0.000358248 * raw^2

Terra d’ Oro, CA (2016-)

VSM = -40.1 + 0.1279569 * raw

Tonzi Ranch, CA

VSM = -33.8015 + 0.1131 * raw

Vaira, CA

VSM = -40.1 + 0.1279569 * raw

*Matthaei Gardens, MI

VSM = -40.1 + 0.1279569 * raw

*Canton, OK

VSM = -40.1 + 0.1279569 * raw

Inactive sites are marked with an asterisk (*)

Data Acquisition, Materials, and Methods

The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at different depths (usually 3-4 depths up to 90 cm) below the soil surface. For newer installations, the sensors were placed at 5cm, 20cm and 50cm depths below the surface. However, when it was not possible to drill down deep enough due to hard soil and rocks, the sensors were installed as deep as possible (up to 30cm or 40cm depth). The sensor was held in place by fastening it to a t-post (Figure 3). A barbed wire fence was also installed around the sensor at some locations to prevent damage from cattle grazing.

sensor node 401 at Tonzi Ranch

Figure 3. View of sensor node 401 at Tonzi Ranch, CA.

 

The sensors communicated with a local coordinator which wirelessly sent the data to the data server located at the University of Southern California (Figure 4).  The optimal placement of the sensors in time and space is achieved using the steady-state soil moisture statistics and surface state distribution of soil moisture in the area of interest weighed against the cost of communication associated with the sensor placement. The system uses the wireless sensor architecture called Ripple (Silva et al., 2012), which has undergone a number of improvement over the years. The current iteration is Ripple 2D+.

soilscape architecture

Figure 4. The wireless architecture of the SoilSCAPE network.

 

Data Access

These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA

Contact for Data Center Access Information:

References

Moghaddam, M., D. Entekhabi, Y. Goykhman, K. Li, M. Liu, A. Mahajan, A. Nayyar, D. Shuman, and D. Teneketzis, A wireless soil moisture smart sensor web using physics-based optimal control: concept and initial demonstration IEEE-JSTARS, vol. 3, no. 4, pp. 522-535, December 2010

Silva, A., M. Liu, and M. Moghaddam, Ripple-2 : A Non-Collaborative, Asynchronous, and Open Architecture for Highly-Scalable and Low Duty-Cycle WSNs. ACM MiSENET, August 2012, Istanbul, Turkey.

Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328

Data Set Revisions

 

Version Description Published
  The SoilSCAPE data were originally published in September 2016. This initial data release contained data from all sites from 2011-08-03 to 2016-07-14. 2016-09-06
R1 The SoilSCAPE data were updated to include measurements through 2016-11-14. 2016-11-22