Vol.3, No.6, 865-870 (2012) Agricultural Sciences
http://dx.doi.org/10.4236/as.2012.36105
Robust and cost-effective system for measuring and
logging of data on soil water content and soil
temperature profile
Mitja Ferlan1,2*, Primoz Simončič2
1University of Ljubljana, Biotechnical Faculty, Ljubljana, Slovenia; *Corresponding Author:
2Slovenian Forestry Institute, Ljubljana, Slovenia
Received 13 June 2012; revised 22 July 2012; accepted 10 August 2012
ABSTRACT
The paper describes the system for measuring
and logging of data on soil water content and
soil temperature profile. The system was tested
in a field and shows great potential for per-
forming continuous measurements. It has sev-
eral benefits including ease of manufacture, low
cost, reliable performance and the ability to
download the data without specialized software.
Keywords: Data-Logger; Soil Temperature; Soil
Water Content; Microcontrollers; Sensors
1. INTRODUCTION
Continuous and automated systems for measuring and
data-logging are needed nowadays in almost every natu-
ral environmental research project. Each natural envi-
ronment or ecosystem is composed of different segments.
For all terrestrial ecosystems, the common segment is
soils, where numerous processes take place. One of the
most important is soil respiration, which is also, after
photosynthetic assimilation, the second largest flux of
carbon and one of the key determinants of net-ecosystem
carbon exchange [1]. To measure soil respiration, the
researchers have used different techniques. Simple but
time consuming technique is using close dynamic or
open dynamic chambers [2] and portable infrared gas
analyzer with an appropriate data logger and system for
pumping air. The weakness of portable system for meas-
uring soil respiration is non-continuous measurements.
One of such portable system for measuring soil respire-
tion with close dynamic chamber is LI-6400 (LI-COR
Biosciences Inc., Lincoln, NE). More complicate and
more expensive but less time consuming is the use of
automated systems for measuring soil respiration (e.g.:
LI-8100, LI-COR Biosciences Inc., Lincoln, NE). Main
feature of these systems is continuous measurements of
soil respiration. Another expensive way to measure soil
respiration is the profile method, but it is not widely used
in comparison with the previously mentioned methods
[3]. In natural environments, high spatial variability, es-
pecially in soils, is not rare and therefore several repeti-
tions of soil respiration measurement are needed. The
main drivers of soil respiration are soil temperature (Ts)
and soil water content (SWC). Continuous measurements
of these two parameters can be relatively easily per-
formed. In the case of using portable systems for meas-
uring soil respiration, we are limited to sensing temporal
variability but in the case of using automated systems we
are limited to sensing spatial variability. Both limitations
can be minimized with additional measurements of Ts
and SWC using apropriate model to gap-fill the data [4].
Spatial and temporal variability of these two parameters
could be observed with an appropriate number of Ts and
SWC profiles. Several profiles mean that many connec-
tions with cables must be made, or alternatively, expen-
sive installation of wireless sensors could be used. Due
to these needs, we have developed, constructed and
tested a robust and cost-effective system for measuring
and data logging Ts and SWC, which is presented in this
paper.
2. SYSTEM DESCRIPTION
The system for measuring and data logging soil water
content and soil temperature profiles is microcontroller-
based with sensors and peripheral components connected
to it. All selected electronic components have low power
consumption and allow battery-powered operation. Cost
estimation and electronic parts of the system are listed in
Table 1.
2.1. Unit for Measuring Soil Water Content
Two frequency domain sensors EC-5 (Decagon De-
vices Inc., Pullman, WA) for measuring soil water con-
tent were used. For correct supply voltage of 2.5 V for

M. Ferlan, P. Simončič / Agricultural Sciences 3 (2012) 865-870
866
Table 1. Part list of the system with cost estimation.
Description Part number Quantity Cost (€)
Conectors Male pins 5 0.50
Voltage regulator REG1117 1 0.40
Memory AT24C512 1 3.40
Microcontroller ATMEGA16 1 4.40
Capacitators 8 0.10
CRYSTAL Clock (32.768 kHz) 1 0.70
Chokes 2 0.20
Resistors 4 0.10
Diode 1N4148 1 0.10
Batery pack 4xAA alkaline 1 5.20
Waterproof enclosure 1 9.50
Circuit boards - 7.40
Cables - 2.00
Mount material - 1.50
Soil water content sensor EC-5 2 130.00
Temperature sensors DS18B20 7 24.50
Serial converter MAX232 1 2.00
the sensors, regulator LD1117 (SGS-THOMSON Mi-
croelectronics) was used. Sensor output ranges from 250
to 1000 mV at a 2.5 V supply voltage and supposed to be
proportional to volumetric soil water content.
The central unit has a built-in 10-bit analog to digital
converter (ADC converter). Therefore only a 100 mH
choke and a 100 nF capacitor must be applied to perform
an accurate voltage reading. Due to this feature, there is
no need to construct a peripheral analog to digital con-
verter and fewer components are needed; consequently
the price is lower. The system described in this paper has
two single ended channels for measuring voltages be-
tween 0 and 2500 mV. Since any other sensors with out-
put signal from 0 to 2500 mV can be used with the pre-
sented system, only an accuracy test of voltage readings
with our system was performed. For this purpose we
used a laboratory voltage generator (Digimaster,
DF1730SB5A) generating voltage in range from 0 to
2500 mV. Voltage was measured with our system and
simultaneously with a laboratory Digital Mutilmeter (M-
3890D-USB, Metex Instruments, Seoul, Korea) con-
nected to a PC for logging. Values were logged every
second. Linear regression between our system and Digi-
tal Mutilmeter was done (n = 1548, R2 = 0.998, slope =
1.002, intercept = −0.188). From these results we can see
that our system underestimates voltage by aproximately
0.2 mV; for equipment that can measure voltage from 0
to 2500 mV this is neglible. From simultaneously meas-
urements accuracy of system voltage measurements was
calculated and it is + −0.22% for testing range.
2.2. Unit for Measuring Temperature
For measuring temperature, most data loggers use dif-
ferential or single-ended voltage measurements and dif-
ferent types of sensors. Most frequently used are ther-
mocouples or thermo-sensitive resistors with negative or
positive temperature coefficients. There are also several
types of integrated circuits which can measure tempera-
ture and convert data to a digital signal. When several
sensors must be used and are connected to the same
measurement and data-logging system, usually at least
two cables per sensor must be used and several voltage
or digital input channels are needed. The system de-
scribed in this paper uses factory calibrated temperature
sensors DS18B20 (Maxim Integrated Products, Sunny-
vale, CA) with ±0.5˚C accuracy in the range between
−10˚C and +85˚C. The sensors use 1-wire communica-
tion protocol (1-Wire is a registered trademark of Maxim
Integrated Products, Inc). The most important feature of
this sensor is that several sensors (up to 100) can be
connected in series on the same cable. Each sensor has a
unique serial number and therefore the central unit can
communicate with a certain sensor and obtain its tem-
perature reading. The cable for short distances can have
one wire for data transfer and power supply and another
for ground; for long distances, one more wire is needed
for power-supply. In any case, the 1-wire protocol re-
quires only one pin for the microcontroller to communi-
cate with several sensors. Reducing the number of cables
reduces the risk of damage to cables (by rodents etc.) and
the risk of loss of data. For measuring a temperature pro-
file in soil, the sensors can be installed on a specially
designed printed circuit with length of 60 cm, according
to World Meteorological Organization (WMO) standards
to sense temperature at elevations of −50 cm, −30 cm,
−20 cm, −10 cm, −5 cm, −2 cm and 5 cm with respect to
the soil surface. The circuit is connected to the data-
logger via a three-wire cable and placed in a plastic tube
with diameter 13 mm and length 65 cm, insulated with
foam. This tube for measurement of soil temperature
profile is easier to install in soil and reduces the potential
damage to temperature sensors. For the placement of the
tube for measuring soil temperature profile in rocky soil,
a drill with appropriate drilling machine could be used,
and in other types of soil an appropriate hand auger
could be used. For sensors placed 5 cm above the ground,
a special home-made radiation shield was used. For
measuring temperature with presented system only 1-
wire sensors DS18B20 could be use, or any other tem-

M. Ferlan, P. Simončič / Agricultural Sciences 3 (2012) 865-870 867
perature sensors with output ranged from 0 to 2500 mV
can be connected to single ended channels. Despite
manufacturer guarantee that sensors are calibrated, we
performed a test with seven temperature sensors placed
in a measurement stick and classical meteorological ther-
mometer (mercury thermometer). As a testing media,
water with ice was used and appropriate hand mixing
was performed. Temperature ranged from 4˚C to 17˚C
and values were logged or manually read every 30 min-
utes. For each temperature sensor, linear regression with
mercury thermometer measurements (n = 12) was made.
From all parameters of linear regression (N = 7), we cal-
culated means and standard deviations (R2 = 0.997 +
−0.001, slope = 0.975 + −0.023, intercept = 0.124 +
−0.377). With these temperature sensors, the temperature
is slightly underestimated compared with the mercury
thermometer. From simultaneously measurements accu-
racy of system temperature measurements was calculated
and it is ±1.1% for testing range.
2.3. Unit for Data Logging
The Philips Inter-IC communications (I2C) protocol
(Philips Semiconductors, The Netherlands) is commonly
used for interfacing peripheral devices and microcon-
trollers. We used this type of communication for data-
logging of nine measured parameters and time stamp on
an AT24C512 (Atmel Corporation, San Jose, CA) mem-
ory module. Measurement frequency in range from 5 to
3600s can be set and system informs us for how many
days the data-logger can store data (For example: meas-
uring frequency set to 30 minutes, the data-logger can
store data for 59 days). If we do not download the data to
an external device (notebook, handheld computer…) and
the memory module is full, the microcontroller stops
measuring and goes into power-down mode.
2.4. Unit for Communication with Other
Devices
The user can communicate with the circuit using ter-
minal software on a notebook or handheld computer.
Communication is available via serial interface (baud
rate: 56,000, Data bits: 8, Parity: none, Stop bits: 1,
Handshaking: none). To establish serial communication
with computer also serial to USB converter could be
used. When connection with the computer is established
the microcontroller program starts a user-interface rou-
tine and displays in the terminal program a notice with
the instructions on how to set up time and date, the loca-
tion of data-logger or download the data. One of the ad-
vantages of the presented system for measuring and
data-logging is that you do not need to install any special
software on your computer. Hyper Terminal (Windows)
or any other free software for reading data from serial
ports can be used.
2.5. Unit for Constant Power Supply with
Battery Pack
The microcontroller circuit is powered by a battery
pack, consisting of four AA-size, 1.5 V alkaline batteries.
Since the microcontroller and other devices (except sen-
sors EC-5 for which a voltage regulator is used) can op-
erate at a voltage between 4.5 and 5.5 V, only a diode
was used in the supply line to avoid short-circuits and to
reduce the voltage from the battery pack. The current
drawn is approximately 15 µA in power save mode and
22 mA during measurement. Each measurement lasts less
than 2 seconds and if the measurement frequency is set
to 30 minutes, using standard AA alkaline batteries, with
a capacity of approximately 2500 mAh, we can expect a
battery life of approximately 5.5 years.
2.6. Central Unit with Real-Time Clock and
Running Program
For the central unit a microcontroller (ATmega16,
Atmel Corporation, San Jose, CA) was used. The AT-
mega16 is a low-power CMOS 8-bit microcontroller
based on the AVR enhanced RISC architecture. The AT-
mega16 offers several functions that allow the construc-
tion of the system with minimum peripheral components,
because of which it is cost-effective and robust. To apply
a real-time clock, the crystal oscillator with 32.768 kHz
frequency must be connected to the microcontroller.
The software for the microcontroller was written in a
BASIC-like language (BASCOM-AVR, MCS Electron-
ics, Holland) for Microsoft Windows XP. The program
was compiled in microcontroller assembly language and
uploaded to the microcontroller using a programmer
(PROGGY AVR, AX Elektronika, Slovenia) connected
to a desktop computer via AVR Studio 4 software (Atmel
Corporation, San Jose, CA).
2.7. System Fabrication and Housing
The system with all its components was built by the
authors, who have also designed the electrical schematic
of the circuit board (Figure 1). The schematic was trans-
ferred to the circuit board, which was drilled out on a
small CNC machine in the laboratory for electronic sys-
tems at the Slovenian Forestry Institute.
Electronic components and connectors were soldered
onto each circuit board and sensor cables were prepared.
The tubes for temperature profile measurements were
prepared according to World Meteorological Organiza-
tion standards. For the fabrication and testing of one sys-
tem approximately 4 hours are required.
The system has a waterproof housing. Three cables for

M. Ferlan, P. Simončič / Agricultural Sciences 3 (2012) 865-870
868
Figure 1. (a) Circuit board with sensors DS18B20 and finished
measurement stick; (b) Microcontroller circuit board with bat-
tery pack; (c) Waterproofed housing with system for measuring
and logging soil temperature profile and soil water content; (d)
Female DB9 connector for serial communication with the sys-
tem built outside.
sensors enter the housing through waterproof cable
glands. The other side of the box houses a female DB9
connector. To protect the female DB9 connector from
humidity and water, a male DB9 connector was made
and used as a waterproof cover. The system housing al-
lows a very convenient field installation and data down-
loading. The schematic is shown on Figure 2, circuit
board (CNC or CAM format) and program (BASIC text
or compiled) are available by contacting the authors.
3. FIELD MEASUREMENTS AND
TESTING OF THE SYSTEM
The system was tested in an abandoned karstic pasture
in SW Slovenia, Europe [5]. Soil respiration measure-
ments were performed under forest and in gaps between
forests [6]. Supporting measurements were performed by
establish six soil water content and temperature profiles.
According to the manual for soil water content sensor
EC-5, measured mV were transformed to % using the
suggested equation for mineral soils with accuracy of +
−5%. Measurements started in February 2010. Precipi-
tation measurements, measurements of soil water content
using two time domain reflectometers (CS616, Campbell
Scientific, Logan, UT USA) inserted horizontally at 10
cm and soil temperature at the same level using thermo-
couples (TCAV, Campbell Scientific, Logan, UT USA)
were made in a nearby meteorological station.
Because of rocky soils, tubes for measuring tempera-
ture profiles were inserted in holes that were drilled into
the soil with a 14 mm diameter drill. The sensors for soil
water content were inserted horizontally into a dug soil
pit (10 and 30 cm depth). One of instalation was done
near meteorological station soil profile, to compare new
system with typical device.
A notebook was used to download data during peri-
odic visits. The data were stored and later imported into
Stata 7.0 software, where they were checked and ap-
pended to the database. In the first few months, small
lead-acid rechargeable batteries (6 V, 1.2 Ah) were used.
The downside of these batteries is high self-discharge
during higher temperatures—because of this, we have
some missing data in April 2010. After replacing the
lead-acid batteries with battery packs, consisting of four
AA 1.5 V alkaline batteries, we did not have any prob-
lems with data loss.
Soil temperature and soil water content data to com-
pare new device with typical device were measured at 10
cm by near meteorological station and dataset of year
2010 was used for comparison. Linear regressions were
performed for temperature and for soil water content
measurements (Ts: R2 = 0.9976, slope = 0.9912, inter-
cept = 0.2744, SWC: R2 = 0.9614, slope = 0.8315, in-
tercept = 0.0338). From these results we can see that our
system systematicly underestimates temperature for apro-
ximately 0.27˚C and overestimate soil water content,
especialy at higher values of this parameter (Figure 3).
Differences in soil water content measurements are aslo
present because construction of EC-5 sensor differ from
CS616 sensor.
Example data for a 14-day period between 16th May
and 29th May is shown in Figure 4.
Concerning the temperature conditions, higher tempo-
ral variability in the plot between forests was observed.
The temperature 5 cm above the ground can be almost
20˚C higher in the plot between forests than in the forest.
On average, mean soil temperature in the forest is 13.5˚C
and the temperature between forests is 1.8˚C higher.
During rain on 21st May, approximately the same tem-
perature was measured in both plots. As far as content of
soil water is concerned, higher values were measured in
the forest. On average, mean soil water content in the
forest period is 8.4% higher (28.7%) in comparison with
the plot between forests (20.3%) during the displayed
period. Also the dynamics of soil water content between
and after rain events are different between plots. This is
especially evident during the vegetation period and dif-
ferences could be observed between plots.

M. Ferlan, P. Simončič / Agricultural Sciences 3 (2012) 865-870 869
Figure 2. Electrical schematic of circuit board.
(a) (b)
Figure 3. Comparison of new system with typical device. (a) Soil water content measuremetns with EC-5 and
CS616; (b) Soil temperature measurements with DS18B20 and TCAV.
After a rain event on 27th May, soil water content in
forest at 30 cm depth (brown line) did not reach as high
level as observed on the plot between forests. Intensive
leaf emergence in the beginning of the vegetation period
was observed after rain on 21st May and the lack of soil
moisture at 30 cm in the forest was due to interception.
Detailed analyses could be drawn from the shown data,
but this would exceed the scope of this study.

M. Ferlan, P. Simončič / Agricultural Sciences 3 (2012) 865-870
870
Figure 4. Example data of soil water content and soil temperature profile for 14-day period between 16th May and 29th May. (a) Soil
temperature profile for plot in forest fragment (air temperature at 5 cm above ground (dark blue line), soil temperature at 2 cm (red
line), 5 cm (green line), 10 cm (purple line), 20 cm (blue line), 30 cm (orange line), 50 cm (grey line)); (b) Soil temperature profile
for plot between forest fragments (air temperature at 5 cm above ground (dark blue line), soil temperature at 2 cm (red line), 5 cm
(green line), 10 cm (purple line), 20 cm (blue line), 30 cm (orange line), 50 cm (grey line)); (c) Soil water content for plot in forest
fragment (soil water content at 10 cm (green line), soil water content at 30 cm (brown line)); (d) Soil water content for plot between
forest fragments (soil water content at 10 cm (green line), soil water content at 30 cm (brown line)).
4. CONCLUSION
The example presents only one aspect of practical use
of the measurements, collected with our system. If we
would install our system into a systematic grid for exam-
ple, we would have a presentation of spatial and tempo-
ral variability in the natural ecosystem. This feature can
be very useful in inhomogeneous ecosystems such as
abandoned extensive pasture. The information collected
using the microcontroller-based system for measuring
and logging of soil water content and temperature profile
has helped with modeling soil respiration between peri-
odic measurements on the abandoned extensive pasture.
Furthermore, with additional analyses of soil in the labo-
ratory, the data from soil temperature profiles will be
used to calculate soil heat flux, which is one of the com-
ponents of the energy balance of the ecosystem.
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